Accepted for/Published in: JMIR Mental Health
Date Submitted: Nov 12, 2020
Date Accepted: Feb 19, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Social representations of e-mental health among the actors of the health care system: a free-association study
ABSTRACT
Background:
Social representations of e-mental health among the actors of the health care system: a free-association study Electronic Mental Health (e-mental Health) offers an opportunity to overcome many challenges such as cost, accessibility and the stigma associated with mental health and most of people with lived experience of mental problems are in favour 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:
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 words and to quantify them by analysing 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 times), "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 in two themes, with technological and computing terms 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 is significantly associated with users. The nursing group uses very medical terms such as "treatment", "diagnosis", "psychiatry", "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 of improvement of their quality of life, and those of health professionals (except nurses) more focused on the technological potential of these digital care tools. The social representation of e-mental health conditions uses and intention of use of which developers, designers, clinicians and users must be aware. 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.
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