Breaking mental health stigma: the impact of online reviews on the adoption of e-mental health platforms

The recent years brought forth a range of innovative services in the field of e-mental health. These services provide online support for psychological distress without the need for physical contact (Rees and Maclaine, 2015). A notable example of such innovation can be found with online psychological counseling (Mannan et al., 2019): Users communicate with psychological professionals through video calls or chat (Wells et al., 2007), which makes this form of intervention a suitable complement to traditional counseling or therapy (Mannan et al., 2019). Moreover, e-mental health platforms have emerged as an accessible and convenient way to connect clients with professionals (Zhou and Wan, 2022).

A significant proportion of individuals with mental health problems do not receive treatment, largely due to limited access to in-person services. Online psychological interventions have the potential to bridge this gap; however, potential users may have limited awareness of available e-mental health services (Mannan et al., 2019). Moreover, individuals might be concerned about data privacy, effectiveness or stigma (Chan et al., 2016; Crisp and Griffiths, 2014; Phillips et al., 2021). They might fear “mental health stigma” as a combination of ignorance, prejudice and discrimination against those affected (Corrigan et al., 2005; Hazell et al., 2022).

It follows that there is a need for investigating the factors influencing e-mental health acceptance and usage. Moreover, the question arises as to how awareness for such stigmatized services can be increased within target groups. We approach these questions from a service marketing perspective: We empirically explore the role of electronic word-of-mouth (eWOM) in the form of online reviews for usage intention regarding platform-based mental health services.

Digitalization provides users with extensive access to health-related information and services. Both providers and users use digital technologies and platforms that enable distant health-care delivery. The growing number of health-care-related touchpoints has led to a generation of consumers who actively use digital information and care options to engage with health-related topics and make informed decisions. These engaged online users serve as a relevant value co-creation element within the service delivery process (Swan et al., 2019).

E-health refers to using information and communication technologies to support health and health care (Hadwich et al., 2010). Likewise, the definition of digital health by the World Medical Association (2022) describes the use of information and communication technologies for therapy and for providing information on health risks and well-being. E-health encompasses different approaches, such as digital patient portals, electronic health records, information portals, monitoring tools, wearables or telemedicine. These offerings have made both access to and exchange of health data more manageable for users. Data is no longer reserved exclusively for health-care providers (Swan et al., 2019). With the rise of smartphones, mobile health (m-health) applications have become essential health-care tools. M-health applications play a key role in transforming daily routines, especially considering habit tracking, goal setting, reminders and health-related searches – which is especially important for users with limited access to traditional health services (Al-Jabali et al., 2025).

A unique form of digitalized health care is the concept of telemedicine, which allows users and providers to interact directly via video, audio or text chat. Despite the advantages of low-threshold, location- and time-independent access, and the positive feedback from existing users, potential providers and users sometimes remain skeptical. Both sides might, for example, doubt the quality of services delivered through digital channels (Swan et al., 2019). Moreover, professionals must rely more heavily on users’ self-reported information. The physical absence thus might complicate assessing users’ individual situation (Roettl et al., 2016; Swan et al., 2019).

Digitalization also led to the development of intervention forms for prevention, treatment and support of psychological distress (Rees and Maclaine, 2015). Literature discusses the provision of digital psychological services as e-mental health, which refers to using information and communication technologies to promote and improve mental health (Weitzel et al., 2023). E-mental health services represent anonymous, low-threshold options to treatment for users reluctant to traditional face-to-face approaches (Apolinário-Hagen et al., 2018b). This includes digital self-help treatments, psychoeducational information, relapse prevention and online psychological counseling via video, audio and text chat – among various other tools and services (Apolinário-Hagen et al., 2018a). The effectiveness of such services was demonstrated in various studies, particularly concerning anxiety disorders, depression and post-traumatic stress (Weitzel et al., 2023). Studies show that users report positive experiences, perceiving e-mental health services as both helpful and satisfactory (Rost et al., 2017; Weitzel et al., 2023). Society increasingly recognizes the importance of e-mental health – especially considering the social distancing and health-care access restrictions experienced during COVID-19 (Ellis et al., 2021; Weitzel et al., 2023).

An additional channel to connect clients with professionals was created by the emergence of mental health platforms. In several consumer categories, platform business models – such as Amazon, Uber and Airbnb – follow the goal of matching demand and supply while creating network effects (Parker et al., 2016). Likewise, online platforms for mental health (OPMH) connect clients with professionals to facilitate the provision of e-mental health services (Zhou and Wan, 2022). Notable examples of OPMH include BetterHelp in the USA, Instahelp in Central Europe or YiXinLi in China (BetterHelp, 2025; Instahelp, 2025; YiXinLi, 2025).

However, the growth of mental health platforms is not as rapid as that of leading platforms in consumer industries. This can be attributed to the fact that health care is strongly regulated. Furthermore, health-care platforms require greater integration of and coordination with traditional offerings from their category (Holgersson et al., 2024). Users generally choose between various counseling methods (audio, video and text chat) and payment models (Zhou and Wan, 2022).

Also referred to as digital mental health (DMH) platforms, these offerings provide a promising channel for the prevention, assessment and support of mental health-related issues (Balcombe and De Leo, 2022). Furthermore, the platform channel allows professionals to provide additional online services alongside their traditional offerings (Zhou and Wan, 2022), thus raising overall market supply.

As a specific form of e-mental health services – and in contrast to automated software tools – online psychological counseling refers to providing a counseling service in which clients and trained professionals directly communicate with each other over the internet (Richards and Richardson, 2012). This form of intervention is especially relevant for clients who are reluctant to face-to-face treatments (Apolinário-Hagen et al., 2018b). Moreover, the limited offer of face-to-face services might be insufficient to meet the high demand (Mannan et al., 2019).

An early exploration of online psychological counseling comes from Manhal-Baugus (2001), who applies the term e-therapy, defined as mental health services provided by a licensed professional via email, video, text chat, virtual reality or any combination of these. This definition emphasizes both the critical role of licensed professionals and the various forms of online communication. Online psychological counseling can serve as a primary form of intervention or as a complement to conventional counseling or therapy (Wells et al., 2007).

Individuals affected by mental health issues often face stigma (Corrigan et al., 2005). The perceived deviation from the norm can lead to stereotyping and discrimination and prevent affected individuals from seeking professional help (Aiyub et al., 2023; Robinson et al., 2018). The far-reaching consequences of mental health stigma, as a combination of ignorance, prejudice and discrimination, have brought forth several anti-stigma campaigns, such as “Time to Change” in the UK (Hazell et al., 2022). The Australian “Act Belong Commit” campaign encourages people to protect and improve their mental health (Donovan et al., 2024). The Austrian project “Healthy Employees – Healthy Company!” (Gesunde MitarbeiterInnen – Gesunder Betrieb!) covered measures to promote mental health in the workplace (Geier and Frech, 2019). Overall, Kemp, Davis et al. (2023) suggest promoting mental health awareness, facilitating access to relevant services and developing government programs and funding to combat stigma and increase motivation to seek help.

Given the stigma surrounding mental health, ensuring low-threshold and anonymous access to mental health services remains crucial. Mental health platforms leverage digital accessibility and anonymity and can help in reducing barriers to seeking help. However, questions remain about how potential users become aware of and develop trust in these emerging services.

In comparison to an extensive body of literature on e-health and related domains (e.g., Chan and Zhuo, 2024; Hadwich et al., 2010), the research landscape surrounding e-mental health appears relatively heterogeneous and fragmented. Several reviews have been published (e.g., Richards and Richardson, 2012; Taylor et al., 2024; Torous et al., 2025), each addressing distinct facets of digital mental health services. Other studies have examined specific aspects such as user attitudes (e.g. Nogueira-Leite et al., 2024), adoption patterns (e.g. Crisp and Griffiths, 2014) or ethical considerations (e.g. Faissner et al., 2024; Manhal-Baugus, 2001).

It is essential to recognize that the term e-mental health encompasses a broad spectrum of interventions, from automated self-care applications to online counseling delivered by licensed professionals. Within this narrower domain, the volume of scholarly literature is comparatively limited. Some authors include the topic within broader systematic reviews (e.g., Zhou et al., 2021), while others address attitude and adoption (e.g. Mannan et al., 2019; Phillips et al., 2021). Notably, literature explicitly addressing online counseling in the context of mental health stigma remains strongly limited (e.g. Apolinário-Hagen et al., 2018a; Withers et al., 2021).

Furthermore, research on the use of transaction platforms for delivering mental health services, as discussed earlier in this paper, is particularly scarce. While some literature can be found on general health-care platforms (e.g. Hermes et al., 2020; Holgersson et al., 2024), only a small number of articles mention the provision of mental health services via such platforms (e.g. Balcombe and De Leo, 2022; Magid et al., 2024; Olawade et al., 2024; Zhou and Wan, 2022). See Table 1 for an overview of relevant articles addressing e-mental health, online counseling, transaction platforms or stigma.

A remarkable number of publications mainly stem from medicine, psychology and related disciplines, representing a lack of insights from a consumer behavior or service marketing perspective. Although research in marketing increasingly addresses the broader e-health sector (e.g. Calegari and Fettermann, 2022; Cuomo et al., 2020; Kovačić et al., 2022; Singh and Ravi, 2022), findings on e-mental health services remain limited. Here, a recent review on mobile health apps found an overwhelming focus on fitness. Mental health services are widely neglected, leading to missed opportunities for insights into adequate e-mental health provision (Al-Jabali et al., 2025).

To the best of our knowledge, literature gaps remain on the provision of online counseling services via platforms against the backdrop of mental health stigma, especially from an online service marketing perspective. We aim to fill these gaps by examining the role of online reviews in shaping users’ intentions to engage with mental health platforms.

Digitization of daily life has profoundly changed the way potential users seek information. Digital access to health-care information has led to remarkable changes, including in the relationship between service providers and users (Cuomo et al., 2020).

Many individuals with mental health-related demands use digital tools to find information online. People search for mental health information as a self-management strategy to better understand their experiences, learn about diagnoses and explore coping strategies (Bucci et al., 2019). A unique role is played by user-generated content (UCG), which can serve as a source of experience for interested potential users (Cuomo et al., 2020). Notably, it has been found that certain users create UCG as a means to destigmatize their mental health treatment journeys, which, in turn, offers support for audiences experiencing similar journeys (Yeh et al., 2025). Such public disclosure can offer guidance, reduce stigma and increase mental health literacy (Zhang et al., 2025). Social media content can help reduce mental health stigma (Griffith and Stein, 2024), whereas TikTok is especially relevant to the mental health discourse for younger generations (Lau et al., 2025). A recent study addressed podcasting as a channel for sharing stories and identified improvements in attitudes and intentions of listeners (Waldman et al., 2024). In line with extant literature, we address another relevant form of user-generated content, which, in marketing, has been identified to provide a broad range of information and opinions, allowing readers a comprehensive comparison: online reviews (Weitzl, 2017).

Across all categories, consumers are increasingly refraining from basing their purchase decisions solely on company-generated information (Lee et al., 2008). Against this backdrop, eWOM plays an increasing role in buying decision processes. eWOM refers to statements made by current or former users about a product or service that are made accessible to a broad audience via the internet (Hennig-Thurau et al., 2004, p. 39). From a marketing perspective, positive word-of-mouth is considered a form of customer engagement behavior by satisfied users, extending beyond repurchase behavior (Malhotra et al., 2022). In contrast, poor customer experiences across cognitive, affective, social, situational or personal dimensions are key drivers of negative word-of-mouth (Ribeiro and Kalro, 2023). The impact of its electronic form (negative eWOM, NeWOM) has been amplified by the rise of social networks and Web 2, which enabled customers to instantly share and access peer reviews (Verma et al., 2023). NeWOM can result in lower purchase intentions, reduced trust or increased switching behavior (Ribeiro and Kalro, 2023).

A review in 2012 already found that eWOM offers several benefits compared to traditional media. Customers perceive it as more persuasive and trustworthy than traditional media, such as radio, TV or print advertising. Interestingly, eWOM is also seen as more effective than traditional word-of-mouth, because of its scalability, accessibility and measurability (Cheung and Thadani, 2012) – notions that are still echoed in more recent literature (Donthu et al., 2021). Of special interest for the underlying paper, researchers are increasingly addressing the important role of positive and negative eWOM in the context of online health care (e.g. Jin and Ryu, 2024; Pauli et al., 2023; Shan et al., 2024).

Online reviews, in particular, are considered a widespread and widely accepted form of eWOM (Hennig-Thurau et al., 2004). In contrast to traditional advertising, online reviews reflect users’ perspectives and include opinions, information and recommendations (Tsao and Hsieh, 2015). Online reviews are considered more trustworthy and objective than traditional advertising messages (Nieto et al., 2014). According to Jiménez and Mendoza (2013), online reviews are the most influential form of eWOM. In the service sector, online reviews represent a critical determinant of users’ willingness to engage with a service. This can be attributed, in part, to the intangibility of services, which amplifies perceived risk. As a result, potential users rely more on peer-generated experiences and evaluations to inform their decision-making process (Reza Jalilvand and Samiei, 2012).

Sussman and Siegal (2003) addressed the question of knowledge transfer in computer-mediated communication and developed the Information Adoption Model (IAM). Specifically, their study addressed the acceptance of information transmitted via email in a professional context.

In essence, the Information Adoption Model posits that the perceived quality of an information and the credibility of the underlying source influence the perceived usefulness of that information. Subsequently, the perceived usefulness leads to information adoption (Sussman and Siegal, 2003), which describes the extent to which recipients evaluate content as meaningful or acceptable (Watts and Zhang, 2008).

The Information Adoption Model is widely recognized and frequently applied as an explanation for the influence of eWOM. It has been used in numerous studies on eWOM, such as in the contexts of hospitality (Cheung et al., 2008), tourism (Leung, 2022; Tapanainen et al., 2021), or e-commerce (Kumar et al., 2023). It provides a solid explanation for the influences and relationships concerning information acceptance and decision-making in computer-mediated processes, of which eWOM is undoubtedly a part (Verma et al., 2023).

Barriers preventing potential users from using online psychological services include lack of awareness, lack of trust or fear of prejudice and stigma. In this context, social media plays a unique role, as younger cohorts spend a significant portion of their time on social media (Kemp, Davis, et al., 2023). Social media users disseminate and consume health-related information through user-generated content (Cuomo et al., 2020). However, a certain level of trust in the credibility of such online information is necessary for decision-making regarding online psychological services (Kemp, Davis, et al., 2023). This notion aligns with Donovan et al. (2024), who highlight the relevance of the perceived credibility of the source of user-generated content.

Against this backdrop, we address the role of online reviews for the intention to use online psychological services by employing the Information Adoption Model. Figure 1 displays our conceptual model incorporating all relevant constructs and hypotheses.

Based on the Elaboration Likelihood Model (Petty and Cacioppo, 1986), the Information Adoption Model (Sussman and Siegal, 2003) posits that the quality of an argument influences whether a recipient is willing to engage cognitively with the information. Argument quality, therefore, refers to the persuasiveness of the arguments embedded within a message (Bhattacherjee and Sanford, 2006), and, thus, the extent to which recipients find the content convincing enough to perform a particular behavior.

Recipients can consider certain reviews of high quality, which leads to the information contained being perceived as useful (Cheung et al., 2009). This notion was also addressed by Mannan and colleagues (2019), who discuss the role of information quality in online mental health service adoption.

Following the Information Adoption Model, we propose that the perceived quality of an information delivered via online reviews influences the perceived usefulness of that information, which leads to H1:

Source credibility refers to a source’s perceived motivation and ability to produce accurate and truthful information (Li and Zhan, 2011). It describes the extent to which the author of a review is considered credible (Levy and Gvili, 2015). Credible sources enable readers to attribute meaning to the information received (Dedeoglu, 2019). As a result, they are more likely to perceive the information as useful and adopt it. In contrast, sources perceived as noncredible increase users’ perceived risk, which may discourage them from following a recommendation (Cheung et al., 2009). The fact that online reviews are often anonymous (Cheung et al., 2009) and can be manipulated by companies (Filieri, 2015), further amplifies the role of source credibility (López and Sicilia, 2014). Credibility is critical in the context of social topics, because these services typically have a greater impact on individual and societal well-being (Donovan et al., 2024). As consumers seek information about mental health services, their perceptions of the credibility of reviews play a crucial role in their decision-making process (Mannan et al., 2019). Against this backdrop, we formulate H2:

Information usefulness refers to the extent to which an information received is perceived as useful and valuable. The Information Adoption Model includes information usefulness as a predictor of potential information adoption (Sussman and Siegal, 2003). This notion is supported by studies across various industries (Cheung et al., 2008; Cheung, 2014; Verma et al., 2023). If recipients consider an information embedded in online reviews as useful, they are more likely to develop the intention to adopt it and incorporate it into their decision-making processes (Cheung et al., 2008). It follows H3:

Information adoption describes the act of actively engaging with and accepting an information provided (Cheung et al., 2008). It is worth noticing that the Information Adoption Model has been criticized for focusing solely on explaining the adoption of information while neglecting subsequent user behavior (Erkan and Evans, 2016).

Building on this critique, Erkan and Evans (2016) expanded the model by developing the Information Acceptance Model (IACM). Among several additional constructs, such as information need or attitude toward information, the IACM discusses information acceptance (similar to information adoption in IAM) as a determinant of purchase intention (Erkan and Evans, 2016).

Empirical findings support the impact of information adoption or acceptance in various contexts. For example, information adoption considering eWOM has been shown to positively influence young travelers’ booking behavior on travel platforms (Song et al., 2021). Against this backdrop, we propose that information adoption (referred to as information acceptance in the IACM) has a positive impact on usage intention, which leads to H4:

We assessed quantitative empirical data via a structured online questionnaire. The target population comprised German-speaking adults residing in the DACH region (Germany, Austria and Switzerland), selected primarily for linguistic and geographic accessibility. Participants were recruited using a convenience sampling approach, primarily via email invitations. Before completing the online questionnaire, participants were presented with the following overview of the concept of online psychological counseling:

We included this information to minimize biases resulting from varying levels of prior knowledge. We further assessed familiarity with the topic and general willingness to use online psychological counseling services. In the next step, all participants were exposed to the same five online reviews of an online psychological counseling service (see Figure 2). Notably, only positive reviews were presented to ensure that valence did not act as a confounding variable. The reviews originated from the OPMH Instahelp. However, participants were not informed about the reviews’ origin, nor were any brand names disclosed in the reviews.

In the next step, participants were asked to rate argument quality (Chong et al., 2018), source credibility (Song et al., 2021; Sussman and Siegal, 2003), information usefulness (Cheung et al., 2008), information adoption (Cheung et al., 2009; Erkan and Evans, 2018) and usage intention (Erkan and Evans, 2016; Song et al., 2021). All constructs were rated using five-point Likert-type scales (see Table 2). The final part of the structured survey consisted of questions regarding demographic characteristics and internet usage behavior. All items were translated to German and pre-tested with a small sample, which resulted in minor linguistic adjustments.

After data cleaning, 280 completed questionnaires (71% female, aged 18–78, mean age 32.3 years) were retained for analysis. Our sample consisted of German-speaking participants from Austria, Germany and Switzerland. In total, 67.9% of participants reported having prior awareness of the concept of online psychological counseling, and 64.6% could generally imagine using such a service if needed.

We applied Structural Equation modeling (SEM) with the software SmartPLS 4 (Ringle et al., 2024). Following the two-step procedure proposed by Anderson and Gerbing (1988), we started by assessing validity and reliability, which was particularly important as the validated English items had to be translated into German for this study.

Factor analysis led to the elimination of two items with factor loadings below the threshold of 0.7. Average variance extracted (AVE) values for all constructs were above 0.5, which further ensured convergent validity. Both Cronbach’s alpha and composite reliability exceeded the threshold of 0.7 (Hair et al., 2016). No square correlations were higher than the AVE, which met the Fornell–Larcker criterion of discriminant validity (see Table 3) (Fornell and Larcker, 1981).

In the second step, we examined the predictive power of our conceptual model and the significance of each path coefficient. All R² values were above the threshold for weak effects of 0.25 (Information Usefulness: 0.659, Information Adoption: 0.348, Usage Intention: 0.354). The effect size f² for each path was above the threshold for medium effects of 0.15 (H1: 0.425, H2: 0.308, H3: 0.533, H4: 0.548) (Hair et al., 2016).

All hypothesized relationships proved significant. Argument quality was found to positively influence information usefulness (β = 0.486, t = 10.519, p < 0.01), confirming H1. H2, which proposed a positive influence of source credibility on information usefulness, was found to be significant and confirmed (β = 0.414, t = 8.670, p < 0.01). H3, which described a positive influence of information usefulness on information adoption, was confirmed (β = 0.590, t = 13.025, p < 0.01). Finally, a positive significant influence of information adoption on usage intention was found (β = 0.595, t = 13.125, p < 0.01), thereby confirming H4 (see Table 4).

To account for potential gender-related differences due to the unequal gender distribution in our sample, we conducted a multi-group analysis (bootstrap MGA) in SmartPLS 4. The results revealed no statistically significant differences related to gender across all hypothesized paths (two-tailed p-values: H1: 0.352, H2: 0.658, H3: 0.956, H4: 0.348).

Although not hypothesized, SEM further allowed us to assess indirect relationships through serial mediation in our conceptual model. The analysis of specific indirect effects provided evidence for a mediated path from argument quality to usage intention (β = 0.171, t = 5.761, p < 0.01) and from source credibility to usage intention (β = 0.145, t = 5.390, p < 0.01).

Misunderstanding and stigma highlight the importance of trust in service providers for potential users’ motivation to adopt e-mental health services (Kemp, Davis, et al., 2023). As interested individuals increasingly turn to user-generated content for health-related information (Cuomo et al., 2020), online reviews can serve as a valuable source of information (Hennig-Thurau et al., 2004).

It is crucial for recipients to perceive online reviews as high-quality to find the information useful (Cheung et al., 2009). Perceived information quality has been identified to positively influence users’ willingness to purchase in tourism (Tapanainen et al., 2021), e-commerce (Kumar et al., 2023), and, importantly, e-mental health (Mannan et al., 2019). In line with prior work, our findings highlight the role of information quality and demonstrate its influence on information usefulness in the context of platform-based online counseling.

However, the usefulness of information found on the internet depends not only on its content but also on its author. More specifically, the credibility of a source of health-related information plays a critical role (Donovan et al., 2024), especially in the context of e-mental health (Mannan et al., 2019). Our findings align with this notion and statistically show the significant influence of source credibility on perceived information usefulness in the context of platform-based online counseling.

To adopt an information, recipients need to consider it useful and valuable (Sussman and Siegal, 2003). In line with findings across various industries (Cheung et al., 2008; Cheung, 2014; Verma et al., 2023), our study demonstrates the significant influence of information usefulness for information adoption in the context of e-mental-health platforms.

Information adoption (Sussman and Siegal, 2003) and information acceptance (Erkan and Evans, 2016) describe participants’ acceptance and engagement with an information provided. Extant literature highlights the role of information adoption for behavioral intentions (Song et al., 2021). Our findings extend prior findings by empirically demonstrating the significant influence of information adoption on usage intention in the context of e-mental health platforms.

Drawing on insights from various disciplines, our article highlights the role of previous users’ reviews in shaping future users’ intentions. To the best of our knowledge, this is one of the first academic publications addressing mental health platforms from a consumer behavior perspective. It complements the body of medical and psychological literature on e-mental health services (Weitzel et al., 2023) with insights from marketing. Furthermore, it extends existing marketing research on the influence of eWOM (Kumar et al., 2023; Tapanainen et al., 2021) by applying it to a mental health platform context.

We recommend that service providers integrate eWOM and online reviews as a relevant component in their communication strategies. To counteract mental health stigma and to increase the motivation to seek support services, it is essential to implement awareness-raising measures and provide low-threshold access to these services (Kemp, Davis, et al., 2023). Easily accessible and anonymous online services combined with targeted information via eWOM can play a crucial role in increasing the adoption of mental health services.

Mental health is often viewed as stigmatized and should be approached with the same awareness and commitment as other health and wellness topics. A key societal challenge is to enhance awareness, improve access to support services and promote targeted campaigns and programs (Kemp, Davis, et al., 2023). In this context, online psychological services can serve as a valuable resource by providing low-threshold interventions and supplementary support options (Emmett et al., 2025). However, lack of awareness, misunderstandings and stigma persist as barriers to adoption (Kemp, Davis, et al., 2023). Potential users increasingly search for mental health-related topics online (Bucci et al., 2019), where user-generated content serves as a relevant source of information (Cuomo et al., 2020).

Against this backdrop, our study explores the role of online reviews for the intention to use platform-based psychological counseling services. Our findings demonstrate how credibility and quality impact the perceived usefulness of an online review, which in turn positively influences information adoption, and, subsequently, usage intention. By strategically leveraging high-quality online reviews – for instance, by encouraging users to share their experiences – e-mental health platforms can not only enhance trust and adoption but also contribute to reducing mental health stigma and improving access to psychological support on a societal scale.

Future researchers are urged to compare the influence of reviews on e-mental health adoption with other communication tools. In addition, future studies could examine whether online reviews primarily influence help-seeking behavior or the choice of a specific service provider. It would also be valuable to investigate the impact of negative or mixed reviews on service adoption in this domain. Finally, future research could compare reviews of online and offline services to identify factors unique to e-mental health.

This study was conducted in accordance with ethical guidelines and the principles of research integrity. Given the anonymous nature of surveys, no personally identifiable information was collected. Informed consent was obtained from all participants, with an emphasis on the voluntary nature of participation and adherence to General Data Protection Regulation guidelines. Participants were assured that their responses would be anonymized, and no attempt would be made to identify individuals based on their survey responses.

The authors disclose that two coauthors are affiliated with the e-mental health platform Instahelp. However, no financial or other conflicts of interest exist. A previous version of this article was published in German in the edited volume Haas-Kotzegger (2025), Digital Economy: Die neuen Spielregeln für Unternehmen.