Leveraging Symptom Search Data to Understand Disparities in US Mental Health Care: Demographic Analysis of Search Engine Trace Data.

BACKGROUND: In the United States, 1 out of every 3 people lives in a mental health professional shortage area. Shortage areas tend to be rural, have higher levels of poverty, and have poor mental health outcomes. Previous work has demonstrated that these poor outcomes may arise from interactions between a lack of resources and lack of recognition of mental illness by medical professionals. OBJECTIVE: We aimed to understand the differences in how people in shortage and nonshortage areas search for information about mental health on the web. METHODS: We analyzed search engine log data related to health from 2017-2021 and examined the differences in mental health search behavior between shortage and nonshortage areas. We analyzed several axes of difference, including shortage versus nonshortage comparisons, urban versus rural comparisons, and temporal comparisons. RESULTS: We found specific differences in search behavior between shortage and nonshortage areas. In shortage areas, broader and more general mental health symptom categories, namely anxiety (mean 2.03%, SD 0.44%), depression (mean 1.15%, SD 0.27%), fatigue (mean 1.21%, SD 0.28%), and headache (mean 1.03%, SD 0.23%), were searched significantly more often (Q<.0003). In contrast, specific symptom categories and mental health disorders such as binge eating (mean 0.02%, SD 0.02%), psychosis (mean 0.37%, SD 0.06%), and attention-deficit/hyperactivity disorder (mean 0.77%, SD 0.10%) were searched significantly more often (Q<.0009) in nonshortage areas. Although suicide rates are consistently known to be higher in shortage and rural areas, we see that the rates of suicide-related searching are lower in shortage areas (mean 0.05%, SD 0.04%) than in nonshortage areas (mean 0.10%, SD 0.03%; Q<.0003), more so when a shortage area is rural (mean 0.024%, SD 0.029%; Q<2 × 10-12). CONCLUSIONS: This study demonstrates differences in how people from geographically marginalized groups search on the web for mental health. One main implication of this work is the influence that search engine ranking algorithms and interface design might have on the kinds of resources that individuals use when in distress. Our results support the idea that search engine algorithm designers should be conscientious of the role that structural factors play in expressions of distress and they should attempt to design search engine algorithms and interfaces to close gaps in care.

Innovations in Technology and Mechanisms of Change in Behavioral Interventions.

The purpose of this manuscript is to provide an overview of, and rationale for, the increasing adoption of a wide range of cutting-edge technological methods in assessment and intervention which are relevant for treatment. First, we review traditional approaches to measuring and monitoring affect, behavior, and cognition in behavior and cognitive-behavioral therapy. Second, we describe evolving active and passive technology-enabled approaches to behavior assessment including emerging applications of digital phenotyping facilitated through fitness trackers, smartwatches, and social media. Third, we describe ways that these emerging technologies may be used for intervention, focusing on novel applications for the use of technology in intervention efforts. Importantly, though some of the methods and approaches we describe here warrant future testing, many aspects of technology can already be easily incorporated within an established treatment framework.

Internet use among persons with common mental disorders: A qualitative study.

Aims and Objectives: To assess the current patterns and experience of internet use among persons with depressive and anxiety disorders, particularly for health-related issues. Methodology: In-depth interviews were conducted with persons diagnosed with depressive and anxiety disorders (DSM-5), aged ≥18 years who could read and write in Hindi/English, using an interview guide. The interview guide contained questions related to internet use in daily life, internet use for health-related issues, and internet use for stress, and internet use for anxiety/depressive disorder. Interview data were transcribed and analyzed to identify codes and subsequently themes. Results: A total of 20 subjects; 10 each diagnosed with depressive and anxiety disorders were interviewed. About half the participants could operate internet independently, while rest required assistance. YouTube was the most common search engine used, and leisure was the most common reason for daily use. Almost all participants reported searching internet for health-related information including their psychiatric diagnosis. The most common purpose, for health in-general, was searching for alternate therapies. Most common purpose for psychiatric diagnosis was understanding the symptoms, recovery from their illness, and side effects of medicines. Highest impact as perceived by the participants was on distraction or stress reduction rather than direct impact on the illness/treatment. Conclusion: Persons with depressive and anxiety disorders use internet for distraction, communication, and seeking information about the illness and medicines.

"Can I Not Be Suicidal on a Sunday?": Understanding Technology-Mediated Pathways to Mental Health Support.

Individuals in distress adopt varied pathways in pursuit of care that aligns with their individual needs. Prior work has established that the first resource an individual leverages can influence later care and recovery, but less is understood about how the design of a point of care might interact with subsequent pathways to care. We investigate how the design of the Indian mental health helpline system interacts with complex sociocultural factors to marginalize caller needs. We draw on interviews with 18 helpline stakeholders, including individuals who have engaged with helplines in the past, shedding light on how they navigate both technological and structural barriers in pursuit of relief. Finally, we use a design justice framework rooted in Amartya Sen's conceptualization of realization-focused justice to discuss implications and present recommendations towards the design of technology-mediated points of mental health support.

Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention.

PURPOSE: Globally, individuals living with mental disorders are more likely to have access to a mobile phone than mental health care. In this commentary, we highlight opportunities for expanding access to and use of digital technologies to advance research and intervention in mental health, with emphasis on the potential impact in lower resource settings. RECENT FINDINGS: Drawing from empirical evidence, largely from higher income settings, we considered three emerging areas where digital technology will potentially play a prominent role: supporting methods in data science to further our understanding of mental health and inform interventions, task sharing for building workforce capacity by training and supervising non-specialist health workers, and facilitating new opportunities for early intervention for young people in lower resource settings. Challenges were identified related to inequities in access, threats of bias in big data analyses, risks to users, and need for user involvement to support engagement and sustained use of digital interventions. SUMMARY: For digital technology to achieve its potential to transform the ways we detect, treat, and prevent mental disorders, there is a clear need for continued research involving multiple stakeholders, and rigorous studies showing that these technologies can successfully drive measurable improvements in mental health outcomes.