MARÍA-CAMINO ESCOLAR-LLAMAZARES

Advances in technology and artificial intelligence (smart healthcare) open up a range of possibilities for precision intervention in the field of health sciences. The objectives of this study were to analyse the functionality of using supervised (prediction and classification) and unsupervised (clustering) machine learning techniques to analyse results related to the development of functional skills in patients at developmental ages of 0–6 years. We worked with a sample of 113 patients, of whom 49 were cared for in a specific centre for people with motor impairments (Group 1) and 64 were cared for in a specific early care programme for patients with different impairments (Group 2). The results indicated that in Group 1, chronological age predicted the development of functional skills at 85% and in Group 2 at 65%. The classification variable detected was functional development in the upper extremities. Two clusters were detected within each group that allowed us to determine the patterns of functional development in each patient with respect to functional skills. The use of smart healthcare resources has a promising future in the field of early care. However, data recording in web applications needs to be planned, and the automation of results through machine learning techniques is required.

The repercussions of the pandemic caused by the SARS-CoV-2 coronavirus over recent years have posed an unprecedented challenge for the whole of society, affecting the well-being of everyone. Among all the variables affected in relation to well-being, Anxiety, Emotional Intelligence, and Effective Personality (Self-Esteem, Academic Self-Realisation, Resolute Self-Efficacy, Social Self-Realisation) have been highlighted. The aim of this study is to assess the evolution of those variables across three temporal phases: pre-pandemic, during the pandemic, and up until the end of the study in April 2022. A study was conducted during these temporal phases with three cohorts from Spanish Universities. The cohorts were formed of people assessed for Anxiety (660 pre-pandemic, 460 during the pandemic, and 311 at the end of the study), Emotional Intelligence (355 pre-pandemic, 91 during the pandemic, 311 at the end of the study), and Effective Personality (708 pre-pandemic, 174 in 2018, 311 at the end of the study). Anxiety was assessed with the State–Trait Anxiety Inventory, Emotional Intelligence with the Trait Meta-Mood Scale and TMMS-24, and Effective Personality with the Cuestionario Personalidad Eficaz-Universidad (the Effective Personality Questionnaire-University). The results showed a rise in the state of anxiety during COVID-19, with a subsequent reduction two years into the pandemic; however, anxiety rates remained higher than before the pandemic. Emotional intelligence increased in the emotional attention factor, but diminished as regards both clarity and regulation. Effective Personality was at lower levels for all factors (Self-Esteem, Academic Self-Realisation, Resolute Self-Efficacy, Social Self-Realisation). The main conclusion was the need for assistance with the dimensions under study, in order to improve the well-being of university students after the serious effects caused by COVID-19.