Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data.

Background: Some of the temporal variations and clock-like rhythms that govern several different health-related behaviors can be traced in near real-time with the help of search engine data. This is especially useful when studying phenomena where little or no traditional data exist. One specific area where traditional data are incomplete is the study of diurnal mood variations, or daily changes in individuals' overall mood state in relation to depression-like symptoms.

Developing Digital Health and Welfare Services in an International Multidisciplinary Student Team.

The rapid growth of digital health and welfare services demands new competences for health and social care, information technology, and business professionals. This study aims to describe the competences that students have before their studies and those they expect to gain from the study module "Developing Digital Health and Welfare Services" in multiprofessional groups during their bachelor studies. This study reports open-ended questions about students' knowledge concerning digital health prior to the study units.