PERSPECTIVE: A Path to Value-Based Insurance Design for Mental Health Services.

BACKGROUND: Aligning cost of mental health care with expected clinical and functional benefits of that care would incentivize the delivery of high value treatments and services. In turn, ineffective or untested care could still be offered but at costs high enough to offset the delivery of high value care. AIMS: The authors comment on Benson and Fendrick's paper on Value-Based Insurance Design (VBID) for mental health in the September 2023 special issue of this journal. The authors also present a preliminary framework of key ingredients needed to consider VBID for mental health treatments and services. METHODS: The authors briefly review current and past efforts to contain costs and improve quality of mental health care, which include (for example) use of carve-out and carve-in programs, evaluation of cost sharing models, impact of accountable care organizations, and studying other benefit designs and impact of federal and state policies. RESULTS: Using PTSD as an example, key ingredients of VBID for mental health services were identified and include the following: tools for case identification and monitoring progress over time at the population level; specific treatments and services with evidence of clinical effectiveness, cost-effectiveness, and health equity; and an approach to document the specific treatment or service was delivered (versus another treatment or service that may lack evidence). DISCUSSION: The inability to afford mental health care is a top barrier to treatment seeking. People who do elect to spend time and money on mental health care are further disadvantaged by accessing care that is not well regulated and the quality at best is questionable. VBID could be an important lever for increasing access to and use of high value mental health care. Partnerships among the research, practice, and policy communities can help ensure research solutions meet needs of these two communities. IMPLICATIONS FOR HEALTH CARE: VBID holds promise to make high value mental health care more affordable while discouraging low value treatments and services. IMPLICATIONS FOR HEALTH POLICIES: While evidence gaps remain, these gaps can be filled concurrently with pursuit of VBID for mental health services. IMPLICATIONS FOR FUTURE RESEARCH: This paper identifies important research opportunities to help make VBID a reality for mental health care.

Comparing Message-Based Psychotherapy to Once-Weekly, Video-Based Psychotherapy for Moderate Depression: Randomized Controlled Trial.

BACKGROUND: Despite the high prevalence of major depressive disorder and the related societal burden, access to effective traditional face-to-face or video-based psychotherapy is a challenge. An alternative that offers mental health care in a flexible setting is asynchronous messaging therapy. To date, no study has evaluated its efficacy and acceptability in a randomized controlled trial for depression. OBJECTIVE: The aim of this study was to compare the efficacy and acceptability of message-based psychotherapy for depression to once-weekly video-based psychotherapy. METHODS: In this 2-armed randomized controlled trial, individuals (N=83) with depressive symptomatology (Patient Health Questionnaire-9 ≥10) were recruited on the internet and randomly assigned to either a message-based intervention group (n=46) or a once-weekly video-based intervention group (n=37). Patients in the message-based treatment condition exchanged asynchronous messages with their therapist following an agreed-upon schedule. Patients in the video-based treatment condition met with their therapist once each week for a 45-minute video teletherapy session. Self-report data for depression, anxiety, and functional impairment were collected at pretreatment, weekly during treatment, at posttreatment, and at a 6-month follow-up. Self-reported treatment expectancy and credibility for the assigned intervention were assessed at pretreatment and therapeutic alliance at posttreatment. RESULTS: Findings from multilevel modeling indicated significant, medium-to-large improvements in depression (d=1.04; 95% CI 0.60-1.46), anxiety (d=0.61; 95% CI 0.22-0.99), and functional impairment (d=0.66; 95% CI 0.27-1.05) for patients in the message-based treatment condition. Changes in depression (d=0.11; 95% CI -0.43 to 0.66), anxiety (d=-0.01; 95% CI -0.56 to 0.53), and functional impairment (d=0.25; 95% CI -0.30 to 0.80) in the message-based treatment condition were noninferior to those in the video-based treatment condition. There were no significant differences in treatment credibility (d=-0.09; 95% CI -0.64 to 0.45), therapeutic alliance (d=-0.15; 95% CI -0.75 to 0.44), or engagement (d=0.24; 95% CI -0.20 to 0.67) between the 2 treatment conditions. CONCLUSIONS: Message-based psychotherapy could present an effective and accessible alternative treatment modality for patients who might not be able to engage in traditional scheduled services such as face-to-face or video-based psychotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT05467787; https://www.clinicaltrials.gov/ct2/show/NCT05467787.

A low-intensity behavioral intervention for depression in older adults delivered by lay coaches: proof-of-concept trial.

OBJECTIVES: A broader workforce is necessary to expand U.S. geriatric mental health services. We examined (1) feasibility of training undergraduate students to deliver Do More, Feel Better (DMFB), an evidence-informed program for depression; and (2) feasibility, acceptability, and outcomes in a single-arm proof-of-concept trial. METHOD: In Study 1, we taught DMFB to 18 upper-level undergraduate students and assessed fidelity using role plays. In Study 2, four students delivered six weekly DMFB sessions to 12 community-dwelling older adults (M = 66.83 years old, SD = 10.39) with depression (PHQ ≥ 10). Patient outcomes were change in pre- to post-treatment depressive symptoms, disability, and the target mechanism of increased activity. RESULTS: Fidelity was high in the course (Study 1; 82.4% of role plays rated as 'passing') and the trial (Study 2; 100% of 24 sessions rated as 'passing'). The majority (83.3%) of patients were retained and evidenced statistically and clinically significant improvement in depressive symptoms (Hamilton Rating Scale for Depression [HAM-D]), disability (World Health Organization's Disability Assessment Schedule 2.0 [WHODAS 2.0], and activity (Behavioral Activation for Depression Scale [BADS]). CONCLUSION: It is feasible to train bachelor's-level students to deliver a brief, structured intervention for depression. Future research should consider implementation strategies and stakeholder feedback.

Acute and intensive care nurses' perspectives on suicide prevention with medically hospitalized patients: Exploring barriers, facilitators, interests, and training opportunities.

AIMS: To explore opportunities for acute and intensive care nurses to engage in suicide prevention activities with patients hospitalized for medical, surgical or traumatic injury reasons. DESIGN: A qualitative descriptive study. METHODS: We conducted two studies consisting of 1-h focus groups with nurses. Study 1 occurred prior to the onset of the COVID-19 pandemic during January and February of 2020 and identified barriers and facilitators of engaging in an eLearning training in suicide safety planning and engaging patients on their units in suicide safety planning. Study 2 occurred in December of 2020 and explored nurses' perspectives on their role in suicide prevention with patients on their units and training needs related to this. The research took place at an urban level 1 trauma center and safety net hospital where nurses universally screen all admitted patients for suicide risk. We conducted a rapid analysis of the focus group transcripts using a top-down, framework-driven approach to identify barriers, facilitators, strategies around barriers, and training interests mentioned. RESULTS: Twenty-seven registered nurses participated. Nurses indicated they serve a population in need of suicide prevention and that the nursing role is an important part of suicide care. A primary barrier was having adequate uninterrupted time for suicide prevention activities and training; however, nurses identified various strategies around barriers and offered suggestions to make training successful. CONCLUSION: Findings suggest training in suicide prevention is important for nurses in this context and there are opportunities for nurses to engage patients in interventions beyond initial screening; however, implementation will require tailoring interventions and training to accommodate nurses' workload in the hospital context. IMPACT: Acute and intensive care nurses play a key role in the public health approach to suicide prevention. Understanding perspectives of bedside nurses is critical for guiding development and deployment of effective brief interventions. NO PUBLIC OR PATIENT INVOLVEMENT: This study is focused on eliciting and exploring perspectives of acute and intensive care nurses.

Modifiable predictors of nonresponse to psychotherapies for late-life depression with executive dysfunction: a machine learning approach.

The study aimed to: (1) Identify distinct trajectories of change in depressive symptoms by mid-treatment during psychotherapy for late-life depression with executive dysfunction; (2) examine if nonresponse by mid-treatment predicted poor response at treatment end; and (3) identify baseline characteristics predicting an early nonresponse trajectory by mid-treatment. A sample of 221 adults 60 years and older with major depression and executive dysfunction were randomized to 12 weeks of either problem-solving therapy or supportive therapy. We used Latent Growth Mixture Models (LGMM) to detect subgroups with distinct trajectories of change in depression by mid-treatment (6th week). We conducted regression analyses with LGMM subgroups as predictors of response at treatment end. We used random forest machine learning algorithms to identify baseline predictors of LGMM trajectories. We found that ~77.5% of participants had a declining trajectory of depression in weeks 0-6, while the remaining 22.5% had a persisting depression trajectory, with no treatment differences. The LGMM trajectories predicted remission and response at treatment end. A random forests model with high prediction accuracy (80%) showed that the strongest modifiable predictors of the persisting depression trajectory were low perceived social support, followed by high neuroticism, low treatment expectancy, and low perception of the therapist as accepting. Our results suggest that modifiable risk factors of early nonresponse to psychotherapy can be identified at the outset of treatment and addressed with targeted personalized interventions. Therapists may focus on increasing meaningful social interactions, addressing concerns related to treatment benefits, and creating a positive working relationship.

Comparing the streamlined psychotherapy "Engage" with problem-solving therapy in late-life major depression. A randomized clinical trial.

Effective psychotherapies for late-life depression are underutilized, mainly because of their complexity. "Engage" is a novel, streamlined psychotherapy that relies on neurobiology to identify core behavioral pathology of late-life depression and targets it with simple interventions, co-designed with community therapists so that they can be delivered in community settings. Consecutively recruited adults (≥60 years) with major depression (n = 249) were randomly assigned to 9 weekly sessions of "Engage" or to the evidence-based Problem-Solving Therapy (PST) offered by 35 trained community social workers and assessed by blind raters. "Engage" therapists required an average of 30% less training time to achieve fidelity to treatment than PST therapists and had one-third of the PST therapists' skill drift. Both treatments led to reduction of HAM-D scores over 9 weeks. The mixed effects model-estimated HAM-D ratings were not significantly different between the two treatments at any assessment point of the trial. The one-sided 95% CI for treatment-end difference was (-∞, 0.07) HAM-D points, indicating a non-inferiority margin of 1.3 HAM-D points or greater; this margin is lower than the pre-determined 2.2-point margin. The two treatment arms had similar response (HR = 1.08, 95% CI (0.76, 1.52), p = 0.67) and remission rates (HR = 0.89, 95% CI (0.57, 1.39), p = 0.61). We conclude that "Engage" is non-inferior to PST. If disseminated, "Engage" will increase the number of therapists who can reliably treat late-life depression and make effective psychotherapy available to large numbers of depressed older adults.

Usability Issues in Evidence-Based Psychosocial Interventions and Implementation Strategies: Cross-project Analysis.

BACKGROUND: People often prefer evidence-based psychosocial interventions (EBPIs) for mental health care; however, these interventions frequently remain unavailable to people in nonspecialty or integrated settings, such as primary care and schools. Previous research has suggested that usability, a concept from human-centered design, could support an understanding of the barriers to and facilitators of the successful adoption of EBPIs and support the redesign of EBPIs and implementation strategies. OBJECTIVE: This study aimed to identify and categorize usability issues in EBPIs and their implementation strategies. METHODS: We adapted a usability issue analysis and reporting format from a human-centered design. A total of 13 projects supported by the National Institute of Mental Health-funded Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center at the University of Washington used this format to describe usability issues for EBPIs and implementation strategies with which they were working. Center researchers used iterative affinity diagramming and coding processes to identify usability issue categories. On the basis of these categories and the underlying issues, we propose heuristics for the design or redesign of EBPIs and implementation strategies. RESULTS: The 13 projects reported a total of 90 usability issues, which we categorized into 12 categories, including complex and/or cognitively overwhelming, required time exceeding available time, incompatibility with interventionist preference or practice, incompatibility with existing workflow, insufficient customization to clients/recipients, intervention buy-in (value), interventionist buy-in (trust), overreliance on technology, requires unavailable infrastructure, inadequate scaffolding for client/recipient, inadequate training and scaffolding for interventionists, and lack of support for necessary communication. These issues range from minor inconveniences that affect a few interventionists or recipients to severe issues that prevent all interventionists or recipients in a setting from completing part or all of the intervention. We propose 12 corresponding heuristics to guide EBPIs and implementation strategy designers in preventing and addressing these usability issues. CONCLUSIONS: Usability issues were prevalent in the studied EBPIs and implementation strategies. We recommend using the lens of usability evaluation to understand and address barriers to the effective use and reach of EBPIs and implementation strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14990.

A Pilot Randomized Trial of Engage Psychotherapy to Increase Social Connection and Reduce Suicide Risk in Later Life.

BACKGROUND: Targeting social connection to prevent suicide in later life shows promise but requires additional study to identify the most effective and acceptable interventions. This study examines acceptability, feasibility, and efficacy of Engage Psychotherapy to improve subjective disconnection (target mechanisms: low belonging and perceived burden), and improve clinical and functional outcomes (depression, suicide ideation, quality of life). METHODS: Pilot randomized trial with adults age 60 and older who reported feeling lonely and/or like a burden. Participants were randomly assigned to 10 sessions of 'Social Engage' (S-ENG; n = 32) or care-as-usual (CAU; n = 30), with follow-up assessments at 3 weeks, 6 weeks, and 10 weeks. RESULTS: S-ENG is feasible to deliver over 10 sessions and acceptable to older adults who report social disconnection-a population at risk for suicide. Participants were willing and able to focus each session on social engagement and demonstrated high levels of compliance. Social Engage did not show preliminary evidence of impact on belonging or perceived burden but was effective in reducing depressive symptoms and improving social-emotional quality of life. DISCUSSION: S-ENG holds promise for improving social-emotional quality of life and depressive symptoms. Future research is needed to identify and measure target mechanisms that account for clinical and functional improvement.

Understanding Psychological Distress and Protective Factors Amongst Older Adults During the COVID-19 Pandemic.

OBJECTIVES: This study examined the emotional distress and loneliness during COVID-19 and the roles of resiliency and activities. DESIGN: A cross-sectional national survey. SETTING: Amazon Mechanical Turk (mTurk) and Prolific Research Platforms. PARTICIPANTS: Five hundred and one U.S. dwelling English-speaking adults 60 years old and older. MEASUREMENTS: Participants completed an online survey with the PHQ-9; GAD-7; Short Health Anxiety Inventory; 3-item UCLA Loneliness scale; PROMIS measures of global health, instrumental, and emotional support; 10-item Connor-Davidson Resilience Scale; and COVID-19 needs assessment. RESULTS: Across the sample 13% reported moderate depressive symptoms, 9% reported moderate anxiety symptoms, and 26% endorsed being "lonely." The emotionally distressed group endorsed more loneliness, lower resiliency, less physical exercise, and worse physical health. The low Socio-Economic Status group endorsed less loneliness, less likely to engage in physical exercise and worse physical health.The lonely group endorsed less resilience, less physical exercise, and worse physical health. A multiple logistic regression found that resilience, socioeconomic status, and physical health were significant predictors of loneliness, whereas global health was the best predictor of emotional distress. CONCLUSIONS: Even after prolonged social distancing, older adults in this study did not report greater psychological distress compared to earlier studies of older adults during COVID-19. Older adults with lower SES, worse physical health, and less resiliency, were more likely to report more loneliness. It is this group that should be the focus of intervention.

Preventing depression in older people with multimorbidity: 24-month follow-up of a trial of internet-delivered cognitive behaviour therapy.

BACKGROUND: older people coping with the impacts of living with multimorbidity are at increased risk of developing a depressive disorder. OBJECTIVE: this article reports the 24-month results of a randomised controlled trial of an internet-delivered cognitive behaviour therapy, which aimed to test whether depressive disorders could be prevented in this population. PARTICIPANTS: community-based participants aged 65 years and over, who had two or more chronic physical health conditions and were assessed as having no current depressive disorder. METHODS: in total, 302 participants were randomised to an 8-week, five-lesson, internet-delivered intervention program (n = 150) or treatment as usual (TAU, n = 152). The primary outcomes were cases of depressive disorder, assessed post-intervention and at 3-month intervals throughout the trial, and depressive symptoms, assessed at pre-intervention, post-intervention, 6, 12 and 24 months following the intervention. RESULTS: there were significantly fewer cases of depressive disorder in the intervention group (n = 23, 15%) compared with the TAU group (n = 41, 27%) during the 24 months after the intervention (χ2(1, N = 302) = 6.13, P = 0.013, odds ratio = 0.490 [95% confidence interval: 0.277, 0.867]), representing a 44% reduction in cases of depressive disorder. No differences were found on depressive symptoms at 24-month follow-up. Internet-delivered cognitive behaviour therapy had high engagement and acceptability. CONCLUSIONS: the results provide support that depressive disorders can be prevented in older people with multimorbidity through participation in internet-delivered cognitive behaviour therapy. With access to internet-delivered interventions in clinical care settings increasing, this has implications for older patient care where multimorbidity is extremely common.

Behavioral Activation and Depression Symptomatology: Longitudinal Assessment of Linguistic Indicators in Text-Based Therapy Sessions.

BACKGROUND: Behavioral activation (BA) is rooted in the behavioral theory of depression, which states that increased exposure to meaningful, rewarding activities is a critical factor in the treatment of depression. Assessing constructs relevant to BA currently requires the administration of standardized instruments, such as the Behavioral Activation for Depression Scale (BADS), which places a burden on patients and providers, among other potential limitations. Previous work has shown that depressed and nondepressed individuals may use language differently and that automated tools can detect these differences. The increasing use of online, chat-based mental health counseling presents an unparalleled resource for automated longitudinal linguistic analysis of patients with depression, with the potential to illuminate the role of reward exposure in recovery. OBJECTIVE: This work investigated how linguistic indicators of planning and participation in enjoyable activities identified in online, text-based counseling sessions relate to depression symptomatology over time. METHODS: Using distributional semantics methods applied to a large corpus of text-based online therapy sessions, we devised a set of novel BA-related categories for the Linguistic Inquiry and Word Count (LIWC) software package. We then analyzed the language used by 10,000 patients in online therapy chat logs for indicators of activation and other depression-related markers using LIWC. RESULTS: Despite their conceptual and operational differences, both previously established LIWC markers of depression and our novel linguistic indicators of activation were strongly associated with depression scores (Patient Health Questionnaire [PHQ]-9) and longitudinal patient trajectories. Emotional tone; pronoun rates; words related to sadness, health, and biology; and BA-related LIWC categories appear to be complementary, explaining more of the variance in the PHQ score together than they do independently. CONCLUSIONS: This study enables further work in automated diagnosis and assessment of depression, the refinement of BA psychotherapeutic strategies, and the development of predictive models for decision support.

Perceived Utility and Characterization of Personal Google Search Histories to Detect Data Patterns Proximal to a Suicide Attempt in Individuals Who Previously Attempted Suicide: Pilot Cohort Study.

BACKGROUND: Despite decades of research to better understand suicide risk and to develop detection and prevention methods, suicide is still one of the leading causes of death globally. While large-scale studies using real-world evidence from electronic health records can identify who is at risk, they have not been successful at pinpointing when someone is at risk. Personalized social media and online search history data, by contrast, could provide an ongoing real-world datastream revealing internal thoughts and personal states of mind. OBJECTIVE: We conducted this study to determine the feasibility and acceptability of using personalized online information-seeking behavior in the identification of risk for suicide attempts. METHODS: This was a cohort survey study to assess attitudes of participants with a prior suicide attempt about using web search data for suicide prevention purposes, dates of lifetime suicide attempts, and an optional one-time download of their past web searches on Google. The study was conducted at the University of Washington School of Medicine Psychiatry Research Offices. The main outcomes were participants' opinions on internet search data for suicide prediction and intervention and any potential change in online information-seeking behavior proximal to a suicide attempt. Individualized nonparametric association analysis was used to assess the magnitude of difference in web search data features derived from time periods proximal (7, 15, 30, and 60 days) to the suicide attempts versus the typical (baseline) search behavior of participants. RESULTS: A total of 62 participants who had attempted suicide in the past agreed to participate in the study. Internet search activity varied from person to person (median 2-24 searches per day). Changes in online search behavior proximal to suicide attempts were evident up to 60 days before attempt. For a subset of attempts (7/30, 23%) search features showed associations from 2 months to a week before the attempt. The top 3 search constructs associated with attempts were online searching patterns (9/30 attempts, 30%), semantic relatedness of search queries to suicide methods (7/30 attempts, 23%), and anger (7/30 attempts, 23%). Participants (40/59, 68%) indicated that use of this personalized web search data for prevention purposes was acceptable with noninvasive potential interventions such as connection to a real person (eg, friend, family member, or counselor); however, concerns were raised about detection accuracy, privacy, and the potential for overly invasive intervention. CONCLUSIONS: Changes in online search behavior may be a useful and acceptable means of detecting suicide risk. Personalized analysis of online information-seeking behavior showed notable changes in search behavior and search terms that are tied to early warning signs of suicide and are evident 2 months to 7 days before a suicide attempt.

Modernizing Training in Psychotherapy Competencies With Adaptive Learning Systems: Proof of Concept.

PURPOSE: This proof-of-concept study assessed the feasibility, acceptability, and effectiveness of an intelligent tutoring system (ITS) as a classroom adjunct to improve training bachelor of social work (BSW) students in client engagement strategies. METHODS: We codeveloped the ITS with 11 undergraduate students and pilot tested it with six BSW students enrolled in a class on telephone-based cognitive behavioral therapy (tCBT). Student competencies in tCBT were assessed by expert review of role-plays. We also examined time spent using ITS and relation with competency. RESULTS: The majority of students (81.8%) in Wave 1 and all of the students who submitted role-plays in Wave 2 passed the clinical skills role-play. Students advancing through the ITS more quickly had better tCBT competency ratings than those progressing more slowly. DISCUSSION: One of the most challenging aspects of training is how to competently deliver evidence-based practices. ITS has the potential to streamline and scale such training.

Resting State Functional Connectivity and Outcomes of Psychotherapies for Late-Life Depression.

BACKGROUND: Problem solving therapy (PST) and "Engage," a reward-exposure" based therapy, are important treatment options for late-life depression, given modest efficacy of antidepressants in this disorder. Abnormal function of the reward and default mode networks has been observed during depressive episodes. This study examined whether resting state functional connectivity (rsFC) of reward and DMN circuitries is associated with treatment outcomes. METHODS: Thirty-two older adults with major depression (mean age = 72.7) were randomized to 9-weeks of either PST or "Engage." We assessed rsFC at baseline and week 6. We placed seeds in three a priori regions of interest: subgenual anterior cingulate cortex (sgACC), dorsal anterior cingulate cortex (dACC), and nucleus accumbens (NAcc). Outcome measures included the Hamilton Depression Rating Scale (HAMD) and the Behavioral Activation for Depression Scale (BADS). RESULTS: In both PST and "Engage," higher rsFC between the sgACC and middle temporal gyrus at baseline was associated with greater improvement in depression severity (HAMD). Preliminary findings suggested that in "Engage" treated participants, lower rsFC between the dACC and dorsomedial prefrontal cortex at baseline was associated with HAMD improvement. Finally, in Engage only, increased rsFC from baseline to week 6 between NAcc and Superior Parietal Cortex was associated with increased BADS scores. CONCLUSION: The results suggest that patients who present with higher rsFC between the sgACC and a structure within the DMN may benefit from behavioral psychotherapies for late life depression. "Engage" may lead to increased rsFC within the reward system reflecting a reconditioning of the reward systems by reward exposure.

Engagement in Socially and Interpersonally Rewarding Activities as a Predictor of Outcome in "Engage" Behavioral Activation Therapy for Late-Life Depression.

OBJECTIVE: Loneliness and social isolation are associated with depressive symptoms, cognitive and physical disabilities, and increased risk of mortality among older adults. Socially rewarding activities reduce loneliness, and neurobiological evidence suggests that these activities may activate neural reward systems in older adults to a greater extent than other rewarding experiences. The current study was designed to investigate whether engagement in social and interpersonal activities (i.e., exposure to social rewards) predicts subsequent increase in behavioral activation and reduction in depressive symptoms in reward exposure treatment for late-life depression. METHODS: Forty-eight older adults without cognitive impairment and with major depression received nine sessions of "Engage" psychotherapy. Behavioral activation and depression severity were assessed by trained raters at baseline and weeks 6 and 9. Patients' weekly behavioral plans were categorized into three groups: 1) solitary activities; 2) social-group activities (attending a social gathering or a social setting such as church or a senior center); and 3) interpersonal-individual activities (engaging in an interpersonal interaction with a specific friend or family member). RESULTS: Mixed-effects models showed reduction in depression severity and increase in behavioral activation over time. In linear regression models, a higher percentage of interpersonal-individual activities (but not solitary or social-group activities) predicted subsequent increase in behavioral activation and improvement of depression. CONCLUSION: These findings highlight the importance of understanding the effects of engagement in specific types of rewarding activities in behavioral activation treatments for late-life depression. Exposure to socially rewarding interpersonal interactions could contribute to the efficacy of psychotherapy for late-life depression.

A Future Research Agenda for Digital Geriatric Mental Healthcare.

The proliferation of mobile, online, and remote monitoring technologies in digital geriatric mental health has the potential to lead to the next major breakthrough in mental health treatments. Unlike traditional mental health services, digital geriatric mental health has the benefit of serving a large number of older adults, and in many instances, does not rely on mental health clinics to offer real-time interventions. As technology increasingly becomes essential in the everyday lives of older adults with mental health conditions, these technologies will provide a fundamental service delivery strategy to support older adults' mental health recovery. Although ample research on digital geriatric mental health is available, fundamental gaps in the scientific literature still exist. To begin to address these gaps, we propose the following recommendations for a future research agenda: 1) additional proof-of-concept studies are needed; 2) integrating engineering principles in methodologically rigorous research may help science keep pace with technology; 3) studies are needed that identify implementation issues; 4) inclusivity of people with a lived experience of a mental health condition can offer valuable perspectives and new insights; and 5) formation of a workgroup specific for digital geriatric mental health to set standards and principles for research and practice. We propose prioritizing the advancement of digital geriatric mental health research in several areas that are of great public health significance, including 1) simultaneous and integrated treatment of physical health and mental health conditions; 2) effectiveness studies that explore diagnostics and treatment of social determinants of health such as "social isolation" and "loneliness;" and 3) tailoring the development and testing of innovative strategies to minority older adult populations.

The accuracy of passive phone sensors in predicting daily mood.

BACKGROUND: Smartphones provide a low-cost and efficient means to collect population level data. Several small studies have shown promise in predicting mood variability from smartphone-based sensor and usage data, but have not been generalized to nationally recruited samples. This study used passive smartphone data, demographic characteristics, and baseline depressive symptoms to predict prospective daily mood. METHOD: Daily phone usage data were collected passively from 271 Android phone users participating in a fully remote randomized controlled trial of depression treatment (BRIGHTEN). Participants completed daily Patient Health Questionnaire-2. A machine learning approach was used to predict daily mood for the entire sample and individual participants. RESULTS: Sample-wide estimates showed a marginally significant association between physical mobility and self-reported daily mood (B = -0.04, P < 0.05), but the predictive models performed poorly for the sample as a whole (median R2 ∼ 0). Focusing on individuals, 13.9% of participants showed significant association (FDR < 0.10) between a passive feature and daily mood. Personalized models combining features provided better prediction performance (median area under the curve [AUC] > 0.50) for 80.6% of participants and very strong prediction in a subset (median AUC > 0.80) for 11.8% of participants. CONCLUSIONS: Passive smartphone data with current features may not be suited for predicting daily mood at a population level because of the high degree of intra- and interindividual variation in phone usage patterns and daily mood ratings. Personalized models show encouraging early signs for predicting an individual's mood state changes, with GPS-derived mobility being the top most important feature in the present sample.

Using Mobile Apps to Assess and Treat Depression in Hispanic and Latino Populations: Fully Remote Randomized Clinical Trial.

BACKGROUND: Most people with mental health disorders fail to receive timely access to adequate care. US Hispanic/Latino individuals are particularly underrepresented in mental health care and are historically a very difficult population to recruit into clinical trials; however, they have increasing access to mobile technology, with over 75% owning a smartphone. This technology has the potential to overcome known barriers to accessing and utilizing traditional assessment and treatment approaches. OBJECTIVE: This study aimed to compare recruitment and engagement in a fully remote trial of individuals with depression who either self-identify as Hispanic/Latino or not. A secondary aim was to assess treatment outcomes in these individuals using three different self-guided mobile apps: iPST (based on evidence-based therapeutic principles from problem-solving therapy, PST), Project Evolution (EVO; a cognitive training app based on cognitive neuroscience principles), and health tips (a health information app that served as an information control). METHODS: We recruited Spanish and English speaking participants through social media platforms, internet-based advertisements, and traditional fliers in select locations in each state across the United States. Assessment and self-guided treatment was conducted on each participant's smartphone or tablet. We enrolled 389 Hispanic/Latino and 637 non-Hispanic/Latino adults with mild to moderate depression as determined by Patient Health Questionnaire-9 (PHQ-9) score≥5 or related functional impairment. Participants were first asked about their preferences among the three apps and then randomized to their top two choices. Outcomes were depressive symptom severity (measured using PHQ-9) and functional impairment (assessed with Sheehan Disability Scale), collected over 3 months. Engagement in the study was assessed based on the number of times participants completed active surveys. RESULTS: We screened 4502 participants and enrolled 1040 participants from throughout the United States over 6 months, yielding a sample of 348 active users. Long-term engagement surfaced as a key issue among Hispanic/Latino participants, who dropped from the study 2 weeks earlier than their non-Hispanic/Latino counterparts (P<.02). No significant differences were observed for treatment outcomes between those identifying as Hispanic/Latino or not. Although depressive symptoms improved (beta=-2.66, P=.006) over the treatment course, outcomes did not vary by treatment app. CONCLUSIONS: Fully remote mobile-based studies can attract a diverse participant pool including people from traditionally underserved communities in mental health care and research (here, Hispanic/Latino individuals). However, keeping participants engaged in this type of "low-touch" research study remains challenging. Hispanic/Latino populations may be less willing to use mobile apps for assessing and managing depression. Future research endeavors should use a user-centered design to determine the role of mobile apps in the assessment and treatment of depression for this population, app features they would be interested in using, and strategies for long-term engagement. TRIAL REGISTRATION: Clinicaltrials.gov NCT01808976; https://clinicaltrials.gov/ct2/show/NCT01808976 (Archived by WebCite at http://www.webcitation.org/70xI3ILkz).

Comparing Approaches to Mobile Depression Assessment for Measurement-Based Care: Prospective Study.

BACKGROUND: To inform measurement-based care, practice guidelines suggest routine symptom monitoring, often on a weekly or monthly basis. Increasingly, patient-provider contacts occur remotely (eg, by telephone and Web-based portals), and mobile health tools can now monitor depressed mood daily or more frequently. However, the reliability and utility of daily ratings are unclear. OBJECTIVE: This study aimed to examine the association between a daily depressive symptom measure and the Patient Health Questionnaire-9 (PHQ-9), the most widely adopted depression self-report measure, and compare how well these 2 assessment methods predict patient outcomes. METHODS: A total of 547 individuals completed smartphone-based measures, including the Patient Health Questionnaire-2 (PHQ-2) modified for daily administration, the PHQ-9, and the Sheehan Disability Scale. Multilevel factor analyses evaluated the reliability of latent depression based on the PHQ-2 (for repeated measures) between weeks 2 and 4 and its correlation with the PHQ-9 at week 4. Regression models predicted week 8 depressive symptoms and disability ratings with daily PHQ-2 and PHQ-9. RESULTS: The daily PHQ-2 and PHQ-9 are highly reliable (range: 0.80-0.88) and highly correlated (r=.80). Findings were robust across demographic groups (age, gender, and ethnic minority status). Daily PHQ-2 and PHQ-9 were comparable in predicting week 8 disability and were independent predictors of week 8 depressive symptoms and disability, though the unique contribution of the PHQ-2 was small in magnitude. CONCLUSIONS: Daily completion of the PHQ-2 is a reasonable proxy for the PHQ-9 and is comparable to the PHQ-9 in predicting future outcomes. Mobile assessment methods offer researchers and clinicians reliable and valid new methods for depression assessment that may be leveraged for measurement-based depression care.

Improving late life depression and cognitive control through the use of therapeutic video game technology: A proof-of-concept randomized trial.

BACKGROUND: Existing treatments for depression are known to have only modest effects, are insufficiently targeted, and are inconsistently utilized, particularly in older adults. Indeed, older adults with impaired cognitive control networks tend to demonstrate poor response to a majority of existing depression interventions. Cognitive control interventions delivered using entertainment software have the potential to not only target the underlying cerebral dysfunction associated with depression, but to do so in a manner that is engaging and engenders adherence to treatment protocol. METHODS: In this proof-of-concept trial (Clinicaltrials.gov #: NCT02229188), individuals with late life depression (LLD) (22; 60+ years old) were randomized to either problem solving therapy (PST, n = 10) or a neurobiologically inspired digital platform designed to enhance cognitive control faculties (Project: EVO™, n = 12). Given the overlapping functional neuroanatomy of mood disturbances and executive dysfunction, we explored the impact of an intervention targeting cognitive control abilities, functional disability, and mood in older adults suffering from LLD, and how those outcomes compare to a therapeutic gold standard. RESULTS: EVO participants demonstrated similar improvements in mood and self-reported function after 4 weeks of treatment to PST participants. The EVO participants also showed generalization to untrained measures of working memory and attention, as well as negativity bias, a finding not evident in the PST condition. Individuals assigned to EVO demonstrated 100% adherence. CONCLUSIONS: This study provides preliminary findings that this therapeutic video game targeting cognitive control deficits may be an efficacious LLD intervention. Future research is needed to confirm these findings.