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Teleconsultations for mental health: Recommendations from a Delphi panel

Authors: Manera VPartos CBeauchet OBenoit MDupetit BElbaum JFabre RGindt MGros AGuerchouche RKlöppel SKönig AMartin AMouton APancrazi MPPolitis ARobert GSacco GSacconi SSawchuk KSolari FThiebot LTrimarchi PDZeghari RRobert P


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Description

Introduction: The use of teleconsultations for mental health has drastically increased since 2020 due to the Covid19 pandemic. In the present paper, we aimed to analyze the advantages and disadvantages of teleconsultations for mental health compared to face-to-face consultations, and to provide recommendations in this domain.

Methods: The recommendations were gathered using a Delphi methodology. The expert panel (N = 21) included professionals from the health and ICT domains. They answered questions via two rounds of web surveys, and then discussed the results in a plenary meeting. Some of the questions were also shared with non-experts (N = 104).

Results: Both the experts and the non-experts with teleconsultation experience reported a general satisfaction concerning teleconsultations. A SWOT analysis revealed several strengths and opportunities of teleconsultations for mental health, but also several weaknesses and threats. The experts provided a set of practical recommendations for the preparation and organization of teleconsultations for mental health.

Discussion: Teleconsultations for mental health have the potential to allow access to care for patients in remote and isolated areas. Thus, their use will unlikely be discontinued after the end of the pandemic. In this context, we suggest that the collaboration among clinicians, researchers, and interface designers is crucial to improve usability and user experience for both clinicians and patients. The importance of teaching teleconsultation skills and informing the public on the features of teleconsultations (e.g., data privacy/security) is also highlighted.


Keywords: Mental healthRecommendationsSWOT analysisTeleconsultationsTelepsychiatry


Links

PubMed: https://pubmed.ncbi.nlm.nih.gov/37655117/

DOI: 10.1016/j.invent.2023.100660