![]() ![]() Many individuals also express concerns over potential privacy and consent issues regarding access to personal mental health-related data 22 and apps storing sensitive information such as account information and demographics, which may discourage their use 23. ![]() There have also been notable concerns regarding the use of mobile apps, potentially excluding groups who may not have access to technology due to cost, digital literacy, location, or availability 21. When assessing the quality and efficacy of smartphone-based interventions as a supplement to treatments or compared to other therapeutic interventions, there have been varying results across treatment groups 20. ![]() ![]() However, there is little information about their utilization, efficacy, and effectiveness 19. Over 10,000 smartphone apps for mental health and well-being are available on the App and Play stores. In the last ten years, technology developers and researchers have begun to explore the potential of smartphone apps as an economical and scalable means for assessing and delivering mental health care. Once validated, these digital signatures can ultimately help track individual physiological symptoms that can be used to tailor and augment the treatment of mental illnesses 18 as well as guide the development of novel treatments for mental health disorders. Multimodal data gathered from connected devices can help understand individualized real-world behavior, aiding the development of digital phenotypes 17. Due to heterogeneity in diagnoses of mental illnesses, researchers are beginning to explore the use of smartphones and wearables 16 in understanding personalized day-to-day factors and their severity impacting individuals’ mental health. Current applications of digital technology in mental health include the remote deployment 14 of guided interventions (e.g., cognitive behavioral therapy 15). In response to such challenges, there is broad interest in using digital health technology to provide individuals with novel preventative and therapeutic solutions in a timely and scalable manner compared to traditional mental health services 13. As a result, our understanding of optimal support and treatment options for underserved and minoritized populations remains limited. Asian, Hispanic, and Black people are less likely to receive access to and utilize mental healthcare services than their White counterparts 10, 11, 12. In particular, there are known socio-technical challenges in recruiting underserved communities 7 such as the Hispanic/Latino population, in traditional research studies 8, 9 in the US. Some populations also do not access care because of the stigma associated with mental health problems 6. In addition, there are known barriers such as time commitment, regular follow-ups in behavioral therapy 4, and limited availability of highly trained professionals, especially in rural and lower-income areas 5. Individuals with depression often lack adequate and timely care, and even when care is available, it is often not evidence-based, and outcomes are not measured consistently 1, 2, 3. A challenge in eradicating this burdensome and costly illness is the poor access to timely diagnosis and treatment. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioral markers and understand the effectiveness of mental health care delivered continuously and remotely.Īlthough effective treatments exist, depression is one of the leading causes of disability worldwide 1. The longitudinal dataset consists of self-assessment of mood, depression, anxiety, and passively gathered phone-based behavioral data streams in real-world settings. The data were generated as part of the two NIMH-funded randomized clinical trials conducted to assess the effectiveness of delivering mental health care continuously remotely. Here we share and describe one of the largest and most diverse real-world behavior datasets from over two thousand individuals across the US. There is a need to create accessible and computable digital mental health datasets to advance inclusive and transparently validated research for creating robust real-world digital biomarkers of mental health. Researchers have been exploring using digital health technologies to measure behavior in real-world settings with mixed results. Most people with mental health disorders cannot receive timely and evidence-based care despite billions of dollars spent by healthcare systems. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |