UTILIZATION OF INFORMATION TECHNOLOGY IN PREVENTION OF DEPRESSION IN OLDER ADULTS

Depression is a problem that often occurs in the older adults population. The use of technology in the implementation of health services has succeeded in increasing the effectiveness and quality of providing health services to patients. Several mobile apps that have been available have the potential to improve services for people with depression. The purpose of this study was to determine the use of information technology in preventing depression in older adults. This study uses a simple literature study method based on a specific theme from several databases including the Cumulative Index to Nursing and Allied Health Literature (CINAHL), ProQuest, and SAGE between 2014 and 2020. 27 journal articles that met the inclusion criteria passed the screening process using the PRISMA diagram. Research showed positive results in the use of technology for depressive conditions experienced by older adults. The importance of developing health applications in order to keep up with the conditions needs to be the attention of health workers. Easy, inexpensive, and attractive health applications can increase public curiosity and participation in the health sector

Health recommender system design in the context of CAREGIVERSPRO-MMD project

CAREGIVERSPRO-MMD an EU H2020 funded project aims to build a digital platform focusing on people living with dementia and their caregivers, offering a selection of advanced, individually tailored services enabling them to live well in the community for as long as possible. This paper provides an outline of a health recommender system designed in the context of the project to provide tailored interventions to caregivers and people living with dementia.Peer ReviewedPostprint (published version

A Smartphone-Based Personalized Activity Recommender System for Patients with Depression

Depression is a common mental illness worldwide. Apart of pharmacological treatment and psychotherapy, self-management of negative emotions is of paramount importance, because relapse of depression often results from an inadequate response to negative emotions. The purpose of this study is to design and implement a personal recommender system, for emotion regulation. It assists users to be aware of negative emotions and guides them to deal with it with behavioral activation. It analyzes the smartphone usage patterns to predict the emergence of negative emotions, while integrating data obtained from context awareness and psychiatrists' recommendations to suggest relevant emotion-regulating activities. In this pilot study, we recruited 15 normal subjects to use our recommender application for 14 days. Our system has successfully recommended activities matched to subjects' intent, and their negative emotions attenuated substantially after engaging in the activities. The presented system has a potential to provide personalized and pervasive mental health services for patients with depression