scholarly journals Design, Recruitment, and Baseline Characteristics of a Virtual 1-Year Mental Health Study on Behavioral Data and Health Outcomes: Observational Study

10.2196/17075 ◽  
2020 ◽  
Vol 7 (7) ◽  
pp. e17075
Author(s):  
Shefali Kumar ◽  
Jennifer L A Tran ◽  
Ernesto Ramirez ◽  
Wei-Nchih Lee ◽  
Luca Foschini ◽  
...  

Background Depression and anxiety greatly impact daily behaviors, such as sleep and activity levels. With the increasing use of activity tracking wearables among the general population, there has been a growing interest in how data collected from these devices can be used to further understand the severity and progression of mental health conditions. Objective This virtual 1-year observational study was designed with the objective of creating a longitudinal data set combining self-reported health outcomes, health care utilization, and quality of life data with activity tracker and app-based behavioral data for individuals with depression and anxiety. We provide an overview of the study design, report on baseline health and behavioral characteristics of the study population, and provide initial insights into how behavioral characteristics differ between groups of individuals with varying levels of disease severity. Methods Individuals who were existing members of an online health community (Achievement, Evidation Health Inc) and were 18 years or older who had self-reported a diagnosis of depression or anxiety were eligible to enroll in this virtual 1-year study. Participants agreed to connect wearable activity trackers that captured data related to physical activity and sleep behavior. Mental health outcomes such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Questionnaire (GAD-7), mental health hospitalizations, and medication use were captured with surveys completed at baseline and months 3, 6, 9, and 12. In this analysis, we report on baseline characteristics of the sample, including mental health disease severity and health care utilization. Additionally, we explore the relationship between passively collected behavioral data and baseline mental health status and health care utilization. Results Of the 1304 participants enrolled in the study, 1277 individuals completed the baseline survey and 1068 individuals had sufficient activity tracker data. Mean age was 33 (SD 9) years, and the majority of the study population was female (77.2%, 994/1288) and identified as Caucasian (88.3%, 1137/1288). At baseline, 94.8% (1211/1277) of study participants reported experiencing depression or anxiety symptoms in the last year. This baseline analysis found that some passively tracked behavioral traits are associated with more severe forms of anxiety or depression. Individuals with depressive symptoms were less active than those with minimal depressive symptoms. Severe forms of depression were also significantly associated with inconsistent sleep patterns and more disordered sleep. Conclusions These initial findings suggest that longitudinal behavioral and health outcomes data may be useful for developing digital measures of health for mental health symptom severity and progression.

2019 ◽  
Author(s):  
Shefali Kumar ◽  
Jennifer L A Tran ◽  
Ernesto Ramirez ◽  
Wei-Nchih Lee ◽  
Luca Foschini ◽  
...  

BACKGROUND Depression and anxiety greatly impact daily behaviors, such as sleep and activity levels. With the increasing use of activity tracking wearables among the general population, there has been a growing interest in how data collected from these devices can be used to further understand the severity and progression of mental health conditions. OBJECTIVE This virtual 1-year observational study was designed with the objective of creating a longitudinal data set combining self-reported health outcomes, health care utilization, and quality of life data with activity tracker and app-based behavioral data for individuals with depression and anxiety. We provide an overview of the study design, report on baseline health and behavioral characteristics of the study population, and provide initial insights into how behavioral characteristics differ between groups of individuals with varying levels of disease severity. METHODS Individuals who were existing members of an online health community (Achievement, Evidation Health Inc) and were 18 years or older who had self-reported a diagnosis of depression or anxiety were eligible to enroll in this virtual 1-year study. Participants agreed to connect wearable activity trackers that captured data related to physical activity and sleep behavior. Mental health outcomes such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Questionnaire (GAD-7), mental health hospitalizations, and medication use were captured with surveys completed at baseline and months 3, 6, 9, and 12. In this analysis, we report on baseline characteristics of the sample, including mental health disease severity and health care utilization. Additionally, we explore the relationship between passively collected behavioral data and baseline mental health status and health care utilization. RESULTS Of the 1304 participants enrolled in the study, 1277 individuals completed the baseline survey and 1068 individuals had sufficient activity tracker data. Mean age was 33 (SD 9) years, and the majority of the study population was female (77.2%, 994/1288) and identified as Caucasian (88.3%, 1137/1288). At baseline, 94.8% (1211/1277) of study participants reported experiencing depression or anxiety symptoms in the last year. This baseline analysis found that some passively tracked behavioral traits are associated with more severe forms of anxiety or depression. Individuals with depressive symptoms were less active than those with minimal depressive symptoms. Severe forms of depression were also significantly associated with inconsistent sleep patterns and more disordered sleep. CONCLUSIONS These initial findings suggest that longitudinal behavioral and health outcomes data may be useful for developing digital measures of health for mental health symptom severity and progression.


2020 ◽  
Vol 75 (1) ◽  
pp. 148-150 ◽  
Author(s):  
Andrea L. Oliverio ◽  
Lindsay K. Admon ◽  
Laura H. Mariani ◽  
Tyler N.A. Winkelman ◽  
Vanessa K. Dalton

2021 ◽  
pp. 135581962199749
Author(s):  
Veronica Toffolutti ◽  
David Stuckler ◽  
Martin McKee ◽  
Ineke Wolsey ◽  
Judith Chapman ◽  
...  

Objective Patients with a combination of long-term physical health problems can face barriers in obtaining appropriate treatment for co-existing mental health problems. This paper evaluates the impact of integrating the improving access to psychological therapies services (IAPT) model with services addressing physical health problems. We ask whether such services can reduce secondary health care utilization costs and improve the employment prospects of those so affected. Methods We used a stepped-wedge design of two cohorts of a total of 1,096 patients with depression and/or anxiety and comorbid long-term physical health conditions from three counties within the Thames Valley from March to August 2017. Panels were balanced. Difference-in-difference models were employed in an intention-to-treat analysis. Results The new Integrated-IAPT was associated with a decrease of 6.15 (95% CI: −6.84 to −5.45) [4.83 (95% CI: −5.47 to −4.19]) points in the Patient Health Questionnaire-9 [generalized anxiety disorder-7] and £360 (95% CI: –£559 to –£162) in terms of secondary health care utilization costs per person in the first three months of treatment. The Integrated-IAPT was also associated with an 8.44% (95% CI: 1.93% to 14.9%) increased probability that those who were unemployed transitioned to employment. Conclusions Mental health treatment in care model with Integrated-IAPT seems to have significantly reduced secondary health care utilization costs among persons with long-term physical health conditions and increased their probability of employment.


2000 ◽  
Vol 3 (3) ◽  
pp. 133-146 ◽  
Author(s):  
Ann F. Garland ◽  
Richard L. Hough ◽  
John A. Landsverk ◽  
Kristen M. McCabe ◽  
May Yeh ◽  
...  

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