Basic Psychological Needs and Motivational Constructs Behind Behavioral Intention Toward Hypothetical Technology-Based Solutions for Loneliness

Abstract Today, loneliness is a widely recognized health concern. Technology offers growing opportunities to develop solutions for mental health challenges. To design effective solutions, this study aims to understand the psychological and motivational factors that influence potential users’ acceptance of hypothetical technology-based approaches to addressing loneliness. Drawing on self-determination theory (SDT) and the two most internalized motivation constructs from the extended unified theory of acceptance and use of technology (UTAUT2), this study examines whether the perceived fulfillment of basic psychological needs (competence, relatedness, and autonomy) is associated with behavioral intentions to adopt technology-based solutions for loneliness at a conceptual level, both directly and indirectly through perceived performance expectancy and perceived hedonic motivation. In this cross-sectional study, data from a nationwide survey in Finland (n = 653) were analyzed using structural equation modeling. The results suggest that satisfaction of basic psychological needs in the context of new technologies is associated with technology acceptance–specific beliefs that may reflect underlying motivational processes as defined by SDT. The findings also highlight the significance of perceived relatedness, perceived performance expectancy, and experienced loneliness, all of which were associated with stronger behavioral intentions toward hypothetical technology-based approaches aimed at alleviating loneliness. The findings suggest that SDT may offer a complementary perspective for technology acceptance research by explaining the psychological and motivational foundations of technology acceptance–specific beliefs. Moreover, in the context of hypothetical technology-based loneliness interventions, respondents appeared to prioritize perceived effectiveness over enjoyment. Further research in real-world settings is needed to assess whether these patterns hold in practice.