Social Representations of e-Mental Health Among the Actors of the Health Care System: Free-Association Study

Background: Electronic mental (e-mental) health offers an opportunity to overcome many challenges such as cost, accessibility, and the stigma associated with mental health, and most people with lived experiences of mental problems are in favor of using applications and websites to manage their mental health problems. However, the use of these new technologies remains weak in the area of mental health and psychiatry. Objective: This study aimed to characterize the social representations associated with e-mental health by all actors to implement new technologies in the best possible way in the health system. Methods: A free-association task method was used. The data were subjected to a lexicometric analysis to qualify and quantify words by analyzing their statistical distribution, using the ALCESTE method with the IRaMuTeQ software. Results: In order of frequency, the terms most frequently used to describe e-mental health in the whole corpus are: care (n=21), internet (n=21), computing (n=15), health (n=14), information (n=13), patient (n=12), and tool (n=12). The corpus of text is divided into 2 themes, with technological and computing terms on one side and medical and public health terms on the other. The largest family is focused on care, advances, research, life, quality, and well-being, which was significantly associated with users. The nursing group used very medical terms such as treatment, diagnosis, psychiatry, and patient to define e-mental health. Conclusions: This study shows that there is a gap between the representations of users on e-mental health as a tool for improving their quality of life and those of health professionals (except nurses) that are more focused on the technological potential of these digital care tools. Developers, designers, clinicians, and users must be aware of the social representation of e-mental health conditions uses and intention of use. This understanding of everyone's stakes will make it possible to redirect the development of tools to adapt them as much as possible to the needs and expectations of the actors of the mental health system.

Automated summary

This study identified the most frequently used terms associated with e-mental health through lexicometric analysis, dividing the text into technological and computing terms, as well as medical and public health terms. The findings revealed a gap between user perceptions of e-mental health as a tool for improving quality of life and healthcare professionals' focus on the technological potential of these digital care tools.