AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients

Abstract

The COVID-19 pandemic has adverse consequences on human psychology and behavior long after initial recovery from the virus. These COVID-19 health sequelae, if undetected and left untreated, may lead to more enduring mental health problems, and put vulnerable individuals at risk of developing more serious psychopathologies. Therefore, an early distinction of such vulnerable individuals from those who are more resilient is important to undertake timely preventive interventions. The main aim of this article is to present a comprehensive multimodal conceptual approach for addressing these potential psychological and behavioral mental health changes using state-of-the-art tools and means of artificial intelligence (AI). Mental health COVID-19 recovery programs at post-COVID clinics based on AI prediction and prevention strategies may significantly improve the global mental health of ex-COVID-19 patients. Most COVID-19 recovery programs currently involve specialists such as pulmonologists, cardiologists, and neurologists, but there is a lack of psychiatrist care. The focus of this article is on new tools which can enhance the current limited psychiatrist resources and capabilities in coping with the upcoming challenges related to widespread mental health disorders. Patients affected by COVID-19 are more vulnerable to psychological and behavioral changes than non-COVID populations and therefore they deserve careful clinical psychological screening in post-COVID clinics. However, despite significant advances in research, the pace of progress in prevention of psychiatric disorders in these patients is still insufficient. Current approaches for the diagnosis of psychiatric disorders largely rely on clinical rating scales, as well as self-rating questionnaires that are inadequate for comprehensive assessment of ex-COVID-19 patients’ susceptibility to mental health deterioration. These limitations can presumably be overcome by applying state-of-the-art AI-based tools in diagnosis, prevention, and treatment of psychiatric disorders in acute phase of disease to prevent more chronic psychiatric consequences.

Update of the Potential Treatments for Psychiatric and Neuropsychiatric Symptoms in the Context of the Post-COVID-19 Condition: Still a Lot of Suffering and Many More Things to Learn

“…This gender effect takes into account that there are four women for every man in the CFS and other gender effects that are known in psychiatric disorders such as anxiety, depression, or PTSD. The number of symptoms at the acute phase is also an important risk factor for developing post-COVID-19, syndrome perhaps because this parameter could reflect the importance of the systemic response [31][32][33][34]. Moreover, a systematic screening of psychiatric and neuropsychiatric symptoms at the acute phase of COVID-19 and targeting circadian dysfunction and encouraging physical activity in people at risk could be efficient ways to reduce psychiatric and neuropsychiatric post-COVID-19 symptoms [32][33][34][39][40][41][42].…”

“…Ćosić et coll. maintained that mental health COVID-19 recovery programs at post-COVID-19 clinics based on AI prediction and prevention strategies may significantly improve the global mental health of ex-COVID-19 patients and that they should be developed [34].…”

Human-Computer Interaction in Digital Mental Health

“…The call for blending clinical and AI approaches in the screening and treatment of psychiatric disorders may potentially boost UCD in AI. The lack of research focusing on the prevention of the sequalae of psychiatric disorders and the vulnerability of ex-COVID patients to mental health disorders led to a conceptual analysis that explored blending clinical approaches (i.e., drawn from clinical rating scales and self-rating questionnaires) with state-of-the-art AI-based tools for expedited and thorough diagnosis, prevention, and treatment of psychiatric disorders [105]. A multimodal psychopathology prediction protocol combined AI methods with comprehensive psychological, neurophysiological, semantic, acoustic, and facial/oculometric measurements and features [105].…”

“…But the lack of use of a HAI framework and the global context of needing more fruitful and efficient strategies in coping with post-COVID overall mental health deterioration requires direction and support. It was suggested that the World Health Organization (WHO) may assist by establishing a multinational interdisciplinary task force for policy design, planning and development of more advanced AI-based innovations in digital psychiatry [105].…”

Students’ study pressures during the Covid-19 global pandemic: exploration of the effects of workload, self-expectation, grade worriness and despondency on college students in Indonesia

“…If the academic pressure on students is high, it will affect their physical, mental and emotional health to various levels and are not conducive to their healthy development and growth. A report on China's educational development in 2019 indicated that excessive study pressure was the main reason for student suicide (Ćosić et al, 2021;N. Li et al, 2022).…”