Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study

Digital phenotyping for mental health based on data analytics: A systematic literature review

Even though mental health is a human right, mental disorders still affect millions of people worldwide. Untreated and undertreated mental health conditions may lead to suicide, which generates more than 700,000 deaths annually around the world. The broad adoption of smartphones and wearable devices allowed the recording and analysis of human behaviors in digital devices, which might reveal mental health symptoms. This analysis constitutes digital phenotyping research, referring to frequent and constant measurement of human phenotypes in situ based on data from smartphones and other personal digital devices. Therefore, this article presents a systematic literature review providing a computer science view on data analytics for digital phenotyping in mental health. This study reviewed 5,422 articles from ten academic databases published up to September 2024, generating a final list of 74 studies. The investigated databases are ACM, IEEE Xplore, PsycArticles, PsycInfo, Pubmed, Science Direct, Scopus, Springer, Web of Science, and Wiley. We investigated ten research questions, considering explored data, employed devices, and techniques for data analysis. This review also organizes the application domains and mental health conditions, data analytics techniques, and current research challenges. This study found a growing research interest in digital phenotyping for mental health in recent years. Current approaches still present a high dependence on self-reported measures of mental health status, but there is evidence of the employment of smartphones for leveraging passive data collection. Traditional machine learning techniques are the main explored strategies for analyzing the large amount of collected data. In this regard, published approaches deeply focused on data analysis, generating opportunities concerning the implementation of resources for assisting individuals suffering from mental disorders.

General Demographics and Behavioral Patterns of Visitors Using a Self-help Website for Identification of and Intervention in Alcoholism and Common Mental Disorders in Suriname: Descriptive Study

Background

Digital health applications have been shown to be an accepted means to provide mental health information and advice in various high- and middle-income countries. Started in 2015, ehealth.sr was the first website to offer preventive information, self-tests, and unguided digital self-help for depression, anxiety symptoms, and problematic alcohol use in Suriname, an upper middle-income country in South America.

Objective

This study aimed to assess the general demographics and behavioral patterns of the visitors of ehealth.sr, as well as to evaluate different promotional channels to attract the target audience to the website.

Methods

Data collection for this study took place between August 2015 and December 2020. Conventional promotion channels such as newspaper and radio advertisements as well as social media advertisements were used to attract users to the website. The number of visits and activity on the website was registered using Google analytics and the website’s internal activity log.

Results

On average, about 115 unique visitors accessed the website per month. The average number of visits to the website increased notably when social media advertisement campaigns were conducted (266 per month in 2018) compared to when traditional advertisements campaigns through papers, radio, and television were used (34 per month in 2019). Of the 1908 new visitors, 1418 (74.32%) were female. On average, visitors accessed 2 (SD 0.3) pages of the website and a session lasted 2.6 (SD 0.9) minutes. The most popular pages for intervention on the website were those for the mood or anxiety screening (731/942, 77.6%) as opposed to those for alcohol screening (211/942, 22.4%). People aged <45 years (on average, 2.2 pages per session for 3.2 minutes) made more use of the website than people aged ≥45 years (on average, 1.7 pages per session for 2 minutes).

Conclusions

Promotion via social media led to more visitors to the website than newspaper or radio advertisements. Younger age groups and females visited the website more often. The pages on preventive information and brief self-tests were visited more frequently than the self-help modules. In general, user adherence to the website in terms of the average session duration and number of viewed pages per session is low and is a key point of concern for the successful implementation of digital mental health websites.