Association Between Care Utilization and Anxiety Outcomes in an On-Demand Mental Health System: Retrospective Observational Study

Generalized anxiety disorder screening scores are associated with greater treatment need among Veterans with depression

Comorbid anxiety and depression predict a poorer prognosis than either disorder occurring alone. It is unclear whether self-reported anxiety symptom scores identify patients with depression in need of more intensive mental health services. This study evaluated how anxiety symptoms predicted treatment receipt and outcomes among patients with new depression diagnoses in the Veterans Health Administration (VHA). Electronic medical record data from 128,917 VHA patients (71.6% assessed for anxiety, n = 92,237) with new diagnoses of depression were analyzed to examine how Generalized Anxiety Disorder-7 (GAD-7) scores predicted psychotropic medication prescriptions, psychotherapy receipt, acute care service utilization, and follow-up depression symptoms. Patients who reported severe symptoms of anxiety were significantly more likely to receive adequate acute phase and continuation phase antidepressant treatment, daytime anxiolytics/sedatives, nighttime sedative/hypnotics, and endorse more severe depression symptoms and suicidal ideation at follow-up. Patients who reported severe symptoms of anxiety at baseline were less likely to initiate psychotherapy. The GAD-7 may help identify depressed patients who have more severe disease burden and require additional mental health services.

Telebehavioral Health for Caregivers of Children With Behavioral Health Needs to Address Caregiver Strain: Cohort Study

BACKGROUND

Behavioral health conditions among children have worsened over the past decade. Caregivers for children with behavioral health conditions are at risk for two types of caregiver strain: (1) an objective strain, that results directly from the child's condition and (2) subjective strain, that arises from the caregiver's feelings regarding these events.

OBJECTIVE

This study aimed to evaluate the impact of a technology-enabled pediatric and family behavioral health service on caregivers' strain among a commercially insured population. We also explore the common symptom clusters of caregiver strain to better understand the caregiver presentation to inform future care planning.

METHODS

We examined changes in caregiver strain using the Caregiver Strain Questionnaire-Short Form 7 over the course of their child's web-based behavioral health care between 2021 and 2023 using a pre-post study design. Common caregiver strain symptom clusters were identified using Ward hierarchical agglomerative clustering.

RESULTS

The majority of children were White 60.8% (1002/1647), female 53.6% (882/1647), and aged between 5 and 9 years (33.7%, 555/1647). Families fall broadly into 4 groups based on what drives caregiver strain the most, namely those experiencing (1) disrupted family relationships and time interruption, (2) missed work, (3) worried about their child's future and feeling tired and sad, and (4) financial strain. Caregiver strain, which was associated with the child's disease severity (P<.001), decreased significantly in all therapeutic groups.

CONCLUSIONS

Web-based family-oriented behavioral health care can improve caregiver strain and reduce family and time disruptions, missed work, and financial strain. Sources of caregiver strain vary and may be overlooked when relying on the conventional scoring of the Caregiver Strain Questionnaire-Short Form 7.

Efficacy of the my health too online cognitive behavioral therapy program for healthcare workers during the COVID-19 pandemic: A randomized controlled trial

Background

Healthcare workers' mental health has been impacted by the COVID-19 pandemic, emphasizing the need for mental health interventions in this population. Online cognitive behavioral therapy (CBT) is efficient to reduce stress and may reach numerous professionals. We developed "MyHealthToo", an online CBT program to help reduce stress among healthcare workers during the COVID-19 pandemic.

Objective

The aim of our study is to investigate the efficacy of an online CBT program on stress and mental health conditions among healthcare workers during a health crisis.

Methods

We performed a multicentric randomized controlled trial among 155 participants allocated either to the experimental or active control group (bibliotherapy). The primary outcome was the decrease of perceived stress scores (PSS-10) post-treatment. Secondary outcomes included depression, insomnia and PTSD symptoms along with self-reported resilience and ruminations. Assessments were scheduled pretreatment, mid-treatment (4 weeks), post-treatment (8 weeks), and at 1-month and 4-months follow-up.

Results

For both interventions, mean changes on the PSS-10 were significant post-therapy (W8), as at 1-month (W12) and 4-months (W24) follow-ups. The between-group comparison showed no difference at any time point (ps > 0.88). Work-related ruminations significantly decreased in the experimental group with a significant between-group difference at W8 (Δ = -1.83 [-3.57; -0.09], p = 0.04). Posttraumatic stress symptoms significantly decreased in the experimental group with a significant between-group difference at W12 (Δ = -1.41 [-2.68; -0.14], p = 0.03). The decrease in work-related ruminations at W8 mediated the decrease in posttraumatic stress symptoms at W12 (p = 0.048).

Conclusion

The "MyHealthToo" online CBT intervention may help reduce ruminations about work and posttraumatic stress symptoms among healthcare workers during a major health crisis. Work-related ruminations may represent a relevant target of online interventions to improve mental health among healthcare workers.

Acceptability and Utility of a Smartphone App to Support Adolescent Mental Health (BeMe): Program Evaluation Study

BACKGROUND

Adolescents face unprecedented mental health challenges, and technology has the opportunity to facilitate access and support digitally connected generations. The combination of digital tools and live human connection may hold particular promise for resonating with and flexibly supporting young people's mental health.

OBJECTIVE

This study aimed to describe the BeMe app-based platform to support adolescents' mental health and well-being and to examine app engagement, usability, and satisfaction.

METHODS

Adolescents in the United States, aged 13 to 20 years, were recruited via the web and enrolled between September 1 and October 31, 2022. App engagement, feature use, clinical functioning, and satisfaction with BeMe were examined for 30 days. BeMe provides content based on cognitive behavioral therapy, dialectical behavior therapy, motivational interviewing, and positive psychology; interactive activities; live text-based coaching; links to clinical services; and crisis support tools (digital and live).

RESULTS

The average age of the sample (N=13,421) was 15.04 (SD 1.7) years, and 56.72% (7612/13,421) identified with she/her pronouns. For the subsample that completed the in-app assessments, the mean scores indicated concern for depression (8-item Patient Health Questionnaire mean 15.68/20, SD 5.9; n=239), anxiety (7-item Generalized Anxiety Disorder Questionnaire mean 13.37/17, SD 5.0; n=791), and poor well-being (World Health Organization-Five Well-being Index mean 30.15/100, SD 16.1; n=1923). Overall, the adolescents engaged with BeMe for an average of 2.38 (SD 2.7) days in 7.94 (SD 24.1) sessions and completed 11.26 (SD 19.8) activities. Most adolescents engaged with BeMe's content (12,270/13,421, 91.42%), mood ratings (13,094/13,421, 97.56%), and interactive skills (10,098/13,421, 75.24%), and almost one-fifth of the adolescents engaged with coaching (2539/13,421, 18.92%), clinical resources (2411/13,421, 17.96%), and crisis support resources (2499/13,421, 18.62%). Overall app engagement (total activities) was highest among female and gender-neutral adolescents compared with male adolescents (all P<.001) and was highest among younger adolescents (aged 13-14 years) compared with all other ages (all P<.001). Satisfaction ratings were generally high for content (eg, 158/176, 89.8% rated as helpful and 1044/1139, 91.66% improved coping self-efficacy), activities (5362/8468, 63.32% helpful and 4408/6072, 72.6% useful in coping with big feelings), and coaching (747/894, 83.6% helpful and 747/894, 83.6% improved coping self-efficacy). Engagement (total activities completed) predicted the likelihood of app satisfaction (P<.001).

CONCLUSIONS

Many adolescents downloaded the BeMe app and completed multiple sessions and activities. Engagement with BeMe was higher among female and younger adolescents. Ratings of BeMe's content, activities, and coaching were very positive for cognitive precursors aimed at reducing depression and anxiety and improving well-being. The findings will inform future app development to promote more sustained engagement, and future evaluations will assess the effects of BeMe on changes in mental health outcomes.

Utilization of digital prenatal services and management of depression and anxiety during pregnancy: A retrospective observational study

Introduction

We examined how utilization of Maven, a digital healthcare platform that provides virtual prenatal services, is associated with improvements in perceived management of anxiety and depression during pregnancy, and how medical knowledge and support may influence this association.

Materials and Methods

In this retrospective study we used adjusted logistic regression to examine the relationship between digital platform use in pregnancy and perceived mental health management, and how perceived management of mental health is affected by user-reported improvements in medical knowledge and feeling supported by the platform. Effects were evaluated separately among users with and without a mental health condition. Demographics, medical history, and mental health management were self-reported.

Results

Of 5,659 users, 705 (12.5%) reported that Maven helped them manage anxiety and/or depression in the prenatal period. In adjusted models, users who read more articles, sent more messages to care advocates, or had more appointments with providers were more likely to report improved management of mental health in a dose-response manner (e.g., articles read: Q2 aOR 1.31 (95% CI 1.01–1.70), Q3 aOR 1.68 (95% CI 1.30–2.17), Q4 1.99 (95% CI 1.54–2.59)). Improvements in medical knowledge and high perceived support were both associated with better perceived mental health management. Results were similar in users with and without a mental health condition.

Discussion

These results suggest that access to a diverse set of digital resources provides multiple pathways to managing depression and anxiety during pregnancy for those with and without a diagnosed mental health condition.

Modern views of machine learning for precision psychiatry

In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and diagnosis of mental disorders. Machine learning (ML) and artificial intelligence (AI) technologies are playing an increasingly critical role in the new era of precision psychiatry. Combining ML/AI with neuromodulation technologies can potentially provide explainable solutions in clinical practice and effective therapeutic treatment. Advanced wearable and mobile technologies also call for the new role of ML/AI for digital phenotyping in mobile mental health. In this review, we provide a comprehensive review of ML methodologies and applications by combining neuroimaging, neuromodulation, and advanced mobile technologies in psychiatry practice. We further review the role of ML in molecular phenotyping and cross-species biomarker identification in precision psychiatry. We also discuss explainable AI (XAI) and neuromodulation in a closed human-in-the-loop manner and highlight the ML potential in multi-media information extraction and multi-modal data fusion. Finally, we discuss conceptual and practical challenges in precision psychiatry and highlight ML opportunities in future research.

Changes in Resilience Following Engagement with A Virtual Mental Health System: A Real World Observational Study (Preprint)

Background

Objective

Methods

Results

Conclusions

Association between Care Modality and Utilization with Treatment Response among Members Accessing Virtual Mental Health Services: A Real-World Observational Study (Preprint)

Background

There is a growing bottleneck in mental health care, as the demand for services has outpaced the availability of mental health professionals. Consequently, many health systems have shifted to teletherapy as a scalable approach to increasing accessibility to care. Within these care models, various treatment modalities (eg, coaching and clinical care) are used to deliver support for anxiety and depression. However, more research is needed to better understand the differences in treatment responses.

Objective

The purpose of this study was to examine the association between different care modalities and the levels of use with symptom score changes for members seeking virtual care services.

Methods

We conducted an observational study of 4219 members who accessed Ginger, an on-demand mental health service, between September 2020 and September 2021. Using a mobile app, members can access text-based behavioral health coaching and virtual clinical services. This study focused on members with clinically elevated depression or anxiety levels at baseline. Logistic regressions were used to assess the association between care modalities and the levels of use with treatment response in depression and anxiety, using the Patient Health Questionnaire and Generalized Anxiety Disorder Assessment, respectively.

Results

Of the 4219 members, 1623 (38.47%) demonstrated a full response to depression, and 1684 (39.91%) demonstrated a full response to anxiety. Members who completed care (ie, text-based coaching, virtual clinical therapy, hybrid of coaching, and clinical care) beyond the introductory session showed significantly increased odds of a full response compared with those who completed only limited care. Members who completed a hybrid of care had the highest odds of improvement; the odds of showing a full response in depression were 2.31 times higher (95% CI 1.91-2.80; P<.001) and in anxiety were 2.23 times higher (95% CI 1.84-2.70; P<.001) compared with members who completed limited care. For members who completed only coaching or clinical care, the largest effects were observed among those with high use. For members who completed a hybrid care program, we observed similar treatment responses across all levels of use.

Conclusions

Our real-world study found that members who completed text-based coaching achieved full treatment responses at similar rates compared with members who completed virtual clinical care and members who completed a hybrid of care. There were no significant differences in the predicted probabilities of full treatment response between coaching and clinical care. Generally, the odds for a full response were highest among members with high use within each care modality; however, there were no differences in full-response treatment odds across levels of use with hybrid care. The results support the utility of digital behavioral health interventions and further highlight text-based coaching protocols as an accessible and suitable option when considering virtual care for treating anxiety and depression.

Changes in healthcare costs following engagement with a virtual mental health system: a matched cohort study of healthcare claims data

The COVID-19 pandemic has exacerbated the pressing need for mental health services. Digital mental health interventions could increase access to care and be an effective approach to reducing anxiety and depression at scale; however, research on their impact on healthcare expenditure is in the nascent stage and requires further investigation. The current study used claims data to examine the associations between use of an on-demand digital mental health platform and healthcare utilization costs compared to a matched control cohort. The study found that there were no significant differences between cohorts in total healthcare costs and pharmacy costs. There was a 16.8% reduction in outpatient costs (p=.08). On-demand digital mental health interventions can serve as a scalable approach to addressing the current mental health demands and potentially lower outpatient costs.

Health-Related Quality of Life among Members using an On-Demand Behavioral Health Platform: A Pilot Observational Study (Preprint)

Background

Despite the well-known adverse health conditions and negative economic outcomes associated with mental health problems, accessing treatment is difficult due to reasons such as availability and cost. As a solution, digital mental health services have flooded the industry, and new studies are quickly emerging that support their potential as an accessible and cost-effective way to improve mental health outcomes. However, many mental health platforms typically use clinical tools such as the Patient Health Questionnaire-9 (PHQ-9) or General Anxiety Disorder-7 (GAD-7). Yet, many individuals that seek out care do not have clinical symptomatology and thus, traditional clinical measures may not adequately capture symptom improvement in general well-being. As an alternative, this study used the health-related quality of life (HRQoL) tool from the Centers for Disease Control and Prevention “Healthy Days” measure. This subjective measure of well-being is an effective way to capture HRQoL and might be better suited as an outcome measure for treatments that include both clinical and subclinical individuals.

Objective

The purpose of this study was to describe changes in HRQoL in clinical and subclinical members assessing virtual care and to examine the association between text-based behavioral coaching and virtual clinical sessions with changes in HRQoL.

Methods

A total of 288 members completed the 4-item HRQoL measure at baseline and at 1 month following use of the Ginger on demand behavioral health platform. Baseline anxiety and depression levels were collected using the GAD-7 and PHQ-9, respectively.

Results

Members completed on average 1.92 (SD 2.16) coaching sessions and 0.91 (SD 1.37) clinical sessions during the assessment month. Paired samples t tests revealed significant reductions in the average number of unhealthy mental health days between baseline (mean 16, SD 8.77 days) and follow-up (mean 13.2, SD 9.02 days; t₂₈₇=5.73; P<.001), and in the average number of days adversely impacted (mean_baseline 10.9, mean_follow-up 8.19; t₂₈₇=6.26; P<.001). Both subclinical members (t₁₀₃=3.04; P=.003) and clinical members (t₁₈₃=5.5; P<.001) demonstrated significant improvements through reductions in adversely impacted days over a month. Clinical members also demonstrated significant improvements through reductions in unhealthy mental health days (t₁₈₃=5.82; P<.001). Finally, member engagement with virtual clinical sessions significantly predicted changes in unhealthy mental health days (B=–0.96; P=.04).

Conclusions

To our knowledge, this study is one of the first to use the HRQoL measure as an outcome in an evaluation of a digital behavioral health platform. Using real-world longitudinal data, our preliminary yet promising results show that short-term engagement with virtual care can be an effective means to improve HRQoL for members with subclinical and clinical symptoms. Further follow-up of reported HRQoL over several months is needed.

Resilience in 2021: Descriptive analysis of individuals accessing virtual mental health services (Preprint)

Background

Psychological resilience has been extensively studied by developmental researchers, and there is a growing body of literature regarding its role in psychiatry and psychopathology research and practice. This study contributes to this growing literature by providing real-world evidence on the relationship between resilience and clinical symptoms among a large sample of employed Americans.

Objective

This study aimed to describe resilience levels in individuals accessing Ginger, a virtual mental health system, in addition to the association of resilience with demographic characteristics, baseline depression, and anxiety symptoms.

Methods

We conducted a retrospective observational study of 9165 members who signed up for Ginger and completed a baseline survey between January 1 and August 5, 2021. We used multivariate regression models to test for associations between baseline resilience and other member characteristics.

Results

Baseline resilience scores centered on a mean of 23.84 (SD 6.56) and median of 24 (IQR 8) out of 40, with 81.0% (7424/9165) of the sample having low resilience at baseline. Despite having relatively higher resilience scores, members with no or mild depression or anxiety still had low resilience scores on average. Self-reported suicidal ideation was associated with lower resilience.

Conclusions

Overall, members had low baseline resilience, similar to resilience levels observed in trauma survivors in prior studies. Younger members and those with higher levels of depression and anxiety at intake reported lower levels of resilience at baseline. Notably, members with no or mild depression or anxiety still had low resilience scores on average, suggesting a need for mental health support among individuals who might not typically be recommended for treatment based on traditional clinical assessments, such as the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item Generalized Anxiety Disorder scale (GAD-7). Two suggestions for topics of future research are to develop treatment recommendations based on the Connor-Davidson Resilience Scale and to understand the interaction between resilience levels and symptom-based outcome measures, such as the PHQ-9 and the GAD-7.