Background: Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients’ needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR. Objective: In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR. Methods: The scoping review followed the framework of Arksey and O’Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR. Results: A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies. Conclusions: Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients’ needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Individuals with schizophrenia spectrum disorders use the Internet for general and health-related purposes. Their ability to find, understand, and apply the health information they acquire online in order to make appropriate health decisions – known as eHealth literacy – has never been investigated. The European agenda strives to limit health inequalities and enhance mental health literacy. Nevertheless, each European member state varies in levels of Internet use and online health information-seeking. This study aimed to examine computer/Internet use for general and health-related purposes, eHealth literacy, and attitudes toward computer/Internet among adults with schizophrenia spectrum disorders from two distant European regions. Data were collected from mental health services of psychiatric clinics in Finland (FI) and Greece (GR). A total of 229 patients (FI = 128, GR = 101) participated in the questionnaire survey. The data analysis included evaluation of frequencies and group comparisons with multiple linear and logistic regression models. The majority of Finnish participants were current Internet users (FI = 111, 87%, vs. GR = 33, 33%, P < .0001), while the majority of Greek participants had never used computers/Internet, mostly due to their perception that they do not need it. In both countries, more than half of Internet users used the Internet for health-related purposes (FI = 61, 55%, vs. GR = 20, 61%). The eHealth literacy of Internet users (previous and current Internet users) was found significantly higher in the Finnish group (FI: Mean = 27.05, SD 5.36; GR: Mean = 23.15, SD = 7.23, P < .0001) upon comparison with their Greek counterparts. For current Internet users, Internet use patterns were significantly different between country groups. When adjusting for gender, age, education and disease duration, country was a significant predictor of frequency of Internet use, eHealth literacy and Interest. The Finnish group of Internet users scored higher in eHealth literacy, while the Greek group of never Internet users had a higher Interest in computer/Internet. eHealth literacy is either moderate (Finnish group) or low (Greek group). Thus, exposure to ICT and eHealth skills training are needed for this population. Recommendations to improve the eHealth literacy and access to health information among these individuals are provided.

Around 20% of those who seek health information online, search specifically for mental health. However, little is known about the nature of the online health information offered by two European countries, Finland and Greece, which are characterized by markedly differing levels of Internet access and online health information seeking. This study aims to assess, describe and compare websites, written in two European, non-English languages (Finnish and Greek) that appear first after performing an online search concerning schizophrenia or related conditions.

Adolescents’ mental health is a global issue and there is a growing interest in tackling mental health in schools. The study aimed to assess secondary school pupils’ mental wellbeing and the factors related to their mental wellbeing (sociodemographic characteristics, perception of belonging to a minority, and discrimination). Data were collected from 12–17-year-old pupils of a Finnish secondary school via an online questionnaire. Data were analyzed with descriptive statistics and ANOVA for group comparisons. Participants’ (Ν = 114) mental wellbeing scores were above average (47.5, max. 70). Worse family relations were independently associated with worse mental wellbeing. Additionally, significantly lower scores on mental wellbeing were found among pupils who thought they belonged to a minority due to appearance, sexual orientation, and/or chronic disease. Participants who had experienced discrimination had significantly lower mental wellbeing scores in comparison to those who never had such an experience. In conclusion, mental health promotion interventions which promote good family relations should be targeting different youth groups in order to address their specific needs. Thus, screening programs which identify pupils who are at risk or belong to minority groups are needed, in order to direct them to proper services when needed and/or implement mental health promotion interventions accordingly.

BACKGROUND Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients’ needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR. OBJECTIVE In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR. METHODS The scoping review followed the framework of Arksey and O’Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR. RESULTS A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies. CONCLUSIONS Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients’ needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.