“I am chatbot, your virtual mental health adviser.” What drives citizens’ satisfaction and continuance intention toward mental health chatbots during the COVID-19 pandemic? An empirical study in China

Abstract

Introduction In order to address the psychological problems during the COVID-19 pandemic, mental health chatbots have been extensively used by public sectors. According to Theory of Consumption Values, this paper proposed an analytical framework to investigate the determinants behind users’ satisfaction and continuance intention toward mental health chatbots. Methods The empirical study was conducted through an online survey, facilitated by the use of questionnaire posted on the WeChat platform. Seven-point Likert scale and closed-ended questions were employed. Totally 371 valid samples were collected. The research data was tested via the partial least squares structural equation modeling. Gender, age, and income were included as control variables. Results Analysis of samples collected from 371 Chinese users suggested that personalization (functional value), enjoyment (emotional value), learning (epistemic value), and the condition of the COVID-19 pandemic (conditional value) have positive influences on user satisfaction and continuance intention, but such effects were weak. The findings also revealed that user satisfaction has weakly positive impact on continuance intention. However, voice interaction (functional value) was an insignificant predictor of user satisfaction and continuance intention. Discussion This study developed a critical perspective on the role of Theory of Consumption Values in the context of mental health chatbot usage, while Theory of Consumption Value has been increasingly employed to explain the use of AI-based public services. Thus, this research devotes to the enhancement of theoretical frameworks regarding the usage of mental health chatbots.

Mobile Applications for the Implementation of Health Control against Covid-19 in Educational Centers, a Systematic Review of the Literature

“…Application Web [11] Artificial Intelligence [12]- [18] Artificial Intelligence and Big Data [19] Big Data [20], [21] BlockChain [22], [23] ChatBot [24] Data Mining [25] Deep Learning [26] Deep Learning and IoT [27]…”

“…[22], [23] This article argues that the use of ChatBots makes it possible to diagnose Covid-19 based on already defined questions, also, they can fulfill the role of informing to obtain better health control against Covid-19, based on truthful information. [24] This article argues that the use of data mining provides accurate information about a query, helps to have real statistics about Covid-19 allowing better health control Covid-19. [25] This article argues that the continuous use of Deep Learning makes it possible to refine it to anticipate responses and/or actions in certain scenarios in which Covid-19 is simulated, thus achieving better health control.…”

“…[29]- [32], [51], [53], [54], [64]- [72], [127] Monitoring [12], [24], [27], [33]- [35], [52], [73]- [88], [90], [92]- [97], [129]- [132] PARAMETERS ARTÍCLES Political [13], [98] Predictive [14]- [17], [19], [25], [26], [37]- [41], [60], [61], [63],…”

“…[12], [24], [27], [33]- [35], [52], [73]- [88], [90], [92]- [97], [129]- [132] These articles take into account the policy parameter as they encourage the use of technological tools in daily life and work so that, in times of pandemic, we adapt to study and work virtually, they also argue to consider very seriously the measures demanded by governments, to prevent Covid-19.…”

“…Availability and functionality [12], [25], [30], [31], [34], [35], [38], [48], [56], [63], [69], [74], [77], [79], [82], [88], [92], [105], [112], [115], [117], [120], [128], [133], [136] Availability, functionality, and reliability [24], [40], [66], [73], [80], [87], [100], [114] Availability, functionality, and performance [11], [16], [29], [46], [62], [86], [110] Availability, functionality, and security [37], [44], [58], [64], [95], [122], [137] Functionality [14], [15],…”