Results of a Qualitative Study Aimed at Building a Programme to Reduce Cardiovascular Risk in People with Severe Mental Illness.

People with severe mental illness (PSMI) have a shorter life expectancy and are more likely to have cardiovascular disease than the general population. Patients, carers, psychiatric professionals and primary care providers can all play a role in increasing PSMI physical health. The present qualitative exploratory study aimed to explore the views of these four populations as part of the multi-phase COPsyCAT project, whose objective is to build and test a cardiovascular risk prevention programme for PSMI. Overall, 107 people participated in the study's 16 focus groups, which were transcribed and analysed in a thematic analysis. With a view to building the health promotion programme, major themes identified in the corpus were translated into a list of needs as follows: communication, information, training and support. Results show that it is essential to improve communication between all the different stakeholders in mental health. The greatest challenge facing this programme will be to adapt it to the needs and expectations of PSMI while facilitating work between the various mental health stakeholders. Simple and inexpensive actions could be taken to improve the cardiovascular health of PSMI and will be experimented with during the programme's feasibility study which will start in September 2022.

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.