Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning.

BACKGROUND: Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory. METHOD: One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics. RESULTS: Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model. CONCLUSIONS: Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Improved outcomes for depressed elder abuse victims with video-delivered psychotherapy during COVID-19.

OBJECTIVE: There is a lack of evidence-based scalable therapies for elder abuse victims, with no current remotely delivered tailored psychotherapy. The purpose of this manuscript is to (a) examine the effectiveness of a brief therapy for depression for elder abuse victims, and (b) to compare remote intervention delivery via phone or video to the traditional in-person delivery. METHOD: PROTECT, Providing Options to Elderly Clients Together, is a brief therapy developed in collaboration with partners at the Department for the Aging (DFTA) of New York City. During the COVID-19 outbreak, PROTECT delivery shifted from in-person to phone or video delivery. Depression severity was tracked using the Patient Health Questionaire-9 (PHQ-9). Reduction in depression severity was evaluated using a linear mixed effects model with non-inferiority test to compare the effectiveness of video vs in-person delivery of PROTECT. RESULTS: PROTECT reduced depression (average 5.15 PHQ-9 points). Video and phone delivery were non-inferior to in-person delivery. The video group completed therapy more quickly than the in-person group and had a more rapid improvement in depression symptoms. CONCLUSIONS: PROTECT therapy delivered remotely reduces depression among diverse elder abuse victims. Video delivery of PROTECT could increase reach and scalability to serve more vulnerable older depressed victims.

Advanced Research Institute (ARI): Supporting the Geriatric Mental Health Research Pipeline.

The Advanced Research Institute (ARI) in Mental Health and Aging is a NIMH-funded mentoring network to help transition early-career faculty to independent investigators and scientific leaders. Since 2004, ARI has enrolled 184 Scholars from 61 institutions across 34 states. We describe the ARI components and assess the impact and outcomes of ARI on research careers of participants. Outcomes of ARI graduates (n = 165) came from NIH Reporter, brief surveys, and CVs: 87.3% remained active researchers, 83.6% performed scientific service, and 80.6% obtained federal grants. A population-based analysis examined NIMH mentored K awardees initially funded from 2002-2018 (n = 1160): in this group, 77.1% (47/61) of ARI participants versus 49.5% (544/1099) of nonparticipants obtained an R01. Controlling for time, ARI participants were 3.2 times more likely to achieve R01 funding than nonparticipants. Given the struggle to reduce attrition from the research career pipeline, the effectiveness of ARI model could be relevant to other fields.

Course of Subtypes of Late-Life Depression Identified by Bipartite Network Analysis During Psychosocial Interventions.

Importance: Approximately half of older adults with depression remain symptomatic at treatment end. Identifying discrete clinical profiles associated with treatment outcomes may guide development of personalized psychosocial interventions. Objective: To identify clinical subtypes of late-life depression and examine their depression trajectory during psychosocial interventions in older adults with depression. Design, Setting, and Participants: This prognostic study included older adults aged 60 years or older who had major depression and participated in 1 of 4 randomized clinical trials of psychosocial interventions for late-life depression. Participants were recruited from the community and outpatient services of Weill Cornell Medicine and the University of California, San Francisco, between March 2002 and April 2013. Data were analyzed from February 2019 to February 2023. Interventions: Participants received 8 to 14 sessions of (1) personalized intervention for patients with major depression and chronic obstructive pulmonary disease, (2) problem-solving therapy, (3) supportive therapy, or (4) active comparison conditions (treatment as usual or case management). Main Outcomes and Measures: The main outcome was the trajectory of depression severity, assessed using the Hamilton Depression Rating Scale (HAM-D). A data-driven, unsupervised, hierarchical clustering of HAM-D items at baseline was conducted to detect clusters of depressive symptoms. A bipartite network analysis was used to identify clinical subtypes at baseline, accounting for both between- and within-patient variability across domains of psychopathology, social support, cognitive impairment, and disability. The trajectories of depression severity in the identified subtypes were compared using mixed-effects models, and time to remission (HAM-D score ≤10) was compared using survival analysis. Results: The bipartite network analysis, which included 535 older adults with major depression (mean [SD] age, 72.7 [8.7] years; 70.7% female), identified 3 clinical subtypes: (1) individuals with severe depression and a large social network; (2) older, educated individuals experiencing strong social support and social interactions; and (3) individuals with disability. There was a significant difference in depression trajectories (F2,2976.9 = 9.4; P < .001) and remission rate (log-rank χ22 = 18.2; P < .001) across clinical subtypes. Subtype 2 had the steepest depression trajectory and highest likelihood of remission regardless of the intervention, while subtype 1 had the poorest depression trajectory. Conclusions and Relevance: In this prognostic study, bipartite network clustering identified 3 subtypes of late-life depression. Knowledge of patients' clinical characteristics may inform treatment selection. Identification of discrete subtypes of late-life depression may stimulate the development of novel, streamlined interventions targeting the clinical vulnerabilities of each subtype.

Research-Practice Partnership to Develop and Implement Routine Mental Health Symptom Tracking Tool Among Older Adults During COVID-19.

OBJECTIVE: Older adults are disproportionally impacted by the COVID-19 pandemic, causing a mental health crisis in late life, due to physical restrictions (e.g., quarantine), limited access to services, and lower literacy and access to technology. Despite established benefits, systematic screening of mental health needs of older adults in community and routine care settings is limited and presents multiple challenges. Cross-disciplinary collaborations are essential for identification and evaluation of mental health needs and service delivery. METHODS: Using a research-practice partnership model, we developed and implemented a routine mental health needs identification and tracking tool at a community-based social services organization. Repeated screenings were conducted remotely over 5 months and included depression, anxiety, perceived loneliness, social support, and related domains such as sleep quality, resilience, and trauma symptoms linked to COVID-19. We examined symptomatic distress levels and associations between different domains of functioning. RESULTS: Our project describes the process of establishing a research-practice partnership during the COVID-19 pandemic. We collected 292 screenings from 124 individuals; clients were mildly to moderately depressed and anxious, reporting large amounts of time alone and moderate levels of loneliness. Those reporting higher depressive symptoms reported higher anxiety symptoms, poorer sleep quality, lower quality of life, lower capacity to adapt to challenging situations, and greater trauma symptoms due to COVID-19. CONCLUSION: Our routine screening tool can serve as a blueprint for case management agencies and senior centers nationwide, beyond the pressing mental health crisis due to COVID-19, to continue identifying needs as they emerge in the community.

Protocol for a collaborative randomised effectiveness trial of lay-delivered versus clinician-delivered behavioural activation in senior centres.

INTRODUCTION: Depression is common among community-dwelling older adults who make use of senior centre services yet remains undertreated due to a lack of acceptable and available treatments. Emerging evidence suggests that lay health providers can offer psychosocial interventions for mental health disorders experienced by older adults. We developed a streamlined Behavioural Activation intervention (called 'Do More, Feel Better'; DMFB) to be delivered by older adult volunteers and propose to compare its effectiveness to that of clinician-delivered behavioural activation (BA). METHODS AND ANALYSIS: This study is a type I collaborative randomised effectiveness trial testing the effect of DMFB in comparison to BA among 288 senior centre clients (aged 60+). Participant clients will be recruited from 6 Seattle, 6 New York City and 6 Tampa area senior centres serving economically and ethnically diverse communities. Primary outcomes will be increased activity level (target) and decreased depressive symptoms. Secondary outcomes will be functioning and client satisfaction, and an exploratory outcome will be treatment fidelity. ETHICS AND DISSEMINATION: The study received ethics approval from the University of Washington Institutional Review Board (STUDY00011434). Client, volunteer and clinician participants will all provide informed consent for study procedures through in-person or remote contact with investigators. Results of this study will be presented in peer-reviewed journals and at professional conferences. TRIAL REGISTRATION NUMBER: NCT04621877; ClinicalTrials.gov.

Use of Passive Sensing in Psychotherapy Studies in Late Life: A Pilot Example, Opportunities and Challenges.

Late-life depression is heterogenous and patients vary in disease course over time. Most psychotherapy studies measure activity levels and symptoms solely using self-report scales, administered periodically. These scales may not capture granular changes during treatment. We introduce the potential utility of passive sensing data collected with smartphone to assess fluctuations in daily functioning in real time during psychotherapy for late life depression in elder abuse victims. To our knowledge, this is the first investigation of passive sensing among depressed elder abuse victims. We present data from three victims who received a 9-week intervention as part of a pilot randomized controlled trial and showed a significant decrease in depressive symptoms (50% reduction). Using a smartphone, we tracked participants' daily number of smartphone unlocks, time spent at home, time spent in conversation, and step count over treatment. Independent assessment of depressive symptoms and behavioral activation were collected at intake, Weeks 6 and 9. Data revealed patient-level fluctuations in activity level over treatment, corresponding with self-reported behavioral activation. We demonstrate how passive sensing data could expand our understanding of heterogenous presentations of late-life depression among elder abuse. We illustrate how trajectories of change in activity levels as measured with passive sensing and subjective measures can be tracked concurrently over time. We outline challenges and potential solutions for application of passive sensing data collection in future studies with larger samples using novel advanced statistical modeling, such as artificial intelligence algorithms.

Modifiable predictors of suicidal ideation during psychotherapy for late-life major depression. A machine learning approach.

This study aimed to identify subgroups of depressed older adults with distinct trajectories of suicidal ideation during brief psychotherapy and to detect modifiable predictors of membership to the trajectories of suicidal ideation. Latent growth mixed models were used to identify trajectories of the presence of suicidal ideation in participants to a randomized controlled trial comparing Problem Solving Therapy with "Engage" therapy in older adults with major depression over 9 weeks. Predictors of membership to trajectories of suicidal ideation were identified by the convergence of four machine learning models, i.e., least absolute shrinkage and selection operator logistic regression, random forest, gradient boosting machine, and classification tree. The course of suicidal ideation was best captured by two trajectories, a favorable and an unfavorable trajectory comprising 173 and 76 participants respectively. Members of the favorable trajectory had no suicidal ideation by week 8. In contrast, members of the unfavorable trajectory had a 60% probability of suicidal ideation by treatment end. Convergent findings of the four machine learning models identified hopelessness, neuroticism, and low general self-efficacy as the strongest predictors of membership to the unfavorable trajectory of suicidal ideation during psychotherapy. Assessment of suicide risk should include hopelessness, neuroticism, and general self-efficacy as they are predictors of an unfavorable course of suicidal ideation in depressed older adults receiving psychotherapy. Psychotherapeutic interventions exist for hopelessness, emotional reactivity related to neuroticism, and low self-efficacy, and if used during therapy, may improve the course of suicidal ideation.

PROTECT: a novel psychotherapy for late-life depression in elder abuse victims.

Elder abuse is prevalent, and victims have high rates of depression and low quality of life. We established an academic-community partnership to test the feasibility, acceptability, and impact of a brief psychotherapy for depression (PROTECT) among elder abuse victims with capacity to make decisions. Elder abuse service providers referred depressed (Patient Health Questionnaire-9 [PHQ-9] ≥ 10) older victims (age ≥ 55 years) for potential pilot study participation. Forty eligible victims who consented were randomized to PROTECT psychotherapy (N = 25) or a Usual Care (N = 15) condition involving a community psychotherapy referral. Follow-up research assessments were conducted at 6 weeks (mid-treatment) and 9 weeks (end of treatment) after study initial assessment. We used mixed-effects regression models to examine treatment effects on depression severity and quality of life over time. Most victims (75%) reported two or more types of abuse. The a priori acceptability benchmark was met at the end of PROTECT therapy. All PROTECT participants initiated therapy; this engagement rate is greater than the a priori 75% standard set for feasibility. We found a significant reduction in depression severity (Montgomery-Åsberg Depression Rating Scale [MADRS]), with PROTECT leading to greater benefits compared to Usual Care. Both study groups had a similar improvement in quality of life. The pilot project results found that PROTECT psychotherapy is feasible, acceptable, and effective in reducing depression. With the support of our partnership, we found that PROTECT could be delivered alongside elder abuse services with victims willing to initiate therapy that leads to meaningful treatment effects.

Perceived Social Support and Interpersonal Functioning as Predictors of Treatment Response Among Depressed Older Adults.

OBJECTIVE: Social isolation is highly common in late life and is associated with devastating mental health and physical outcomes. This study investigated whether components of social isolation (marital status, perceived social support, and interpersonal problems) predict change in depression severity over the course of a brief adherence intervention delivered in a primary care setting. METHOD: A sample of 189 older adults with major depressive disorder were randomized to either an adherence intervention, "Treatment Initiation Program," or treatment as usual. Marital status, perceived social support and interpersonal problems were assessed at baseline. A mixed-effects regression was used to test whether these factors predicted the change trajectory in depression severity over 24 weeks. RESULTS: Being married (F(2,176) = 6.60; p = 0.001), reporting higher perceived social support (F(2,177) = 4.70; p = 0.01), and fewer interpersonal problems (F(2, 176) = 4.34; p = 0.01) predicted lower depression severity on average over the course of 24 weeks. CONCLUSION: Social variables such as living in partnership, perceiving others as supportive, and reporting few interpersonal problems may reduce older adults' vulnerability to depression and enhance their ability to benefit from treatment. These findings can guide development of interventions that will target these social factors early in treatment to increase efficacy.

The Relationship Between Maladaptive Personality and Social Role Impairment in Depressed Older Adults in Primary Care.

Objective: Personality pathology is associated with impaired social functioning in adults, though further evidence is needed to examine the individual contributions of personality traits and processes to social functioning in depressed older adults. This study is a secondary analysis examining the relationship between maladaptive personality traits and processes and social role impairment in depressed older adults in primary care. Methods: Participants (N = 56) were 77% female and ranged in age between 55-89 (M = 66.82, SD = 8.75). Personality pathology was measured by maladaptive traits (NEO-FFI) and processes (Inventory of Interpersonal Problems; IIP-PD-15). Individual variable as well as combined predictive models of social role impairment were examined. Results: Higher neuroticism (ß = 0.30, p < .05), lower agreeableness (ß = -0.35 p < .001) and higher IIP-PD-15 (ß = 0.28, p < .01) scores predicted greater impairment in social role functioning. A combined predictive model of neuroticism and IIP-PD-15 scores predicted unique variance in social role impairment (R2 = .71). Conclusion: These results link select personality traits and interpersonal processes to social role impairment, suggesting that these are indicators of personality pathology in older adults. Clinical Implications: These findings lend preliminary support for clinical screening of personality pathology in depressed older adults utilizing both personality trait and process measures.

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.

Associations between unmet palliative care needs and cognitive impairment in a sample of diverse, community-based older adults.

OBJECTIVE: Given a large number of community-based older adults with mild cognitive impairment, it is essential to better understand the relationship between unmet palliative care (PC) needs and mild cognitive impairment in community-based samples. METHOD: Participants consisted of adults ages 60+ receiving services at senior centers located in New York City. The Montreal Cognitive Assessment (MoCA) and the Unmet Palliative Care Needs screening tool were used to assess participants' cognitive status and PC needs. RESULTS: Our results revealed a quadratic relationship between unmet PC needs and mild cognitive impairment, controlling for gender, living status, and age. Participants with either low or high MoCA scores reported lower PC needs than participants with average MoCA scores, mean difference of the contrast (low and high vs. middle) = 2.15, P = 0.08. SIGNIFICANCE OF RESULTS: This study is a first step toward elucidating the relationship between cognitive impairment and PC needs in a diverse community sample of older adults. More research is needed to better understand the unique PC needs of older adults with cognitive impairment living in the community.

Community delivery of brief therapy for depressed older adults impacted by Hurricane Sandy.

Older adults frequently under-report depressive symptoms and often fail to access services after a disaster. To address unmet mental health needs, we developed a service delivery program (SMART-MH) that combines outreach, assessment, and therapy and implemented it in New York City after Hurricane Sandy. This study aimed to examine the feasibility, effectiveness, and patients' engagement of our brief psychotherapy ("Engage"). We predicted that Engage would result in reductions of depression, and that the benefits would be comparable to those of a historical comparison group who received Engage in a controlled experimental setting. A total of 2,831 adults (age ≥ 60) impacted by Hurricane Sandy were screened for depression. Assessments and therapy were conducted in English, Spanish, Cantonese, and Russian. Depressed individuals (PHQ-9 ≥ 10) who were not in treatment were offered Engage therapy in their native language at local senior center/nutrition sites. Twelve percent of the participants reported depression (N = 333). Of these 333 participants, 201 (60%) were not receiving treatment and 143 agreed to receive Engage therapy. Linear mixed-effects model showed that depression severity decreased significantly over time. More than two thirds had a five-point reduction in PHQ-9 scores and post-treatment scores ≤9. Post-hoc comparison of standardized slopes of change found patterns of depression reductions equivalent to Engage provided in a controlled setting. Partnerships to integrate mental health care into community settings can increase detection of mental-health needs and access to services in patients' native language. Brief reward exposure-based psychotherapy delivered in the community can provide comparable benefits to those achieved in research settings.

Integrated behavioral health treatments: innovations to achieve population impact.

Translational Behavioral Medicine is a journal that brings together relevant scholars and practitioners to produce articles of scientific and practical significance in a variety of fields. Here, we published a call for manuscripts detailing the study of innovations in the field of implementation of integrated care in the USA. We present 13 articles, all peer reviewed and all targeting some aspect of integrated care implementation. These articles include medical and community-based settings, as well as interventions that effectively engage peers, family members, and other social systems to support and extend care. The behavioral health conditions of interest include but were not limited to those that carry the greatest population disease burdens: depression, posttraumatic stress disorder, bipolar disorder, anxiety disorders, and substance abuse disorders. Examples of cross-cutting issues of high interest include research focused on provider and system barriers to integrated care implementation, interventions to improve the use of innovative treatments, disparities in access to care and quality of treatment, the intersection of behavioral health disorders and complex chronic conditions as it affects regimen adherence, health services organization and quality of care, policy effects, innovative methods using health information and mHealth technologies, and personalized/precision medicine. This introduction briefly summarizes some of the relevant topics and background literature. We close with an eye toward future research activities that will continue to advance the field and offer directions to stimulate new research questions in the area.

Treatment Adequacy and Adherence as Predictors of Depression Response in Primary Care.

OBJECTIVE: Primary care is the de facto mental health system in the United States where physicians treat large numbers of depressed older adults with antidepressant medication. This study aimed to examine whether antidepressant dosage adequacy and patient adherence are associated with depression response among middle-aged and older adults prescribed with antidepressants by their primary care provider. DESIGN: A secondary analysis was conducted on a sample drawn from a randomized controlled trial comparing Treatment as Usual to Treatment Initiation Program, an adherence intervention. Treatment Initiation Program improved adherence but not depression compared to Treatment as Usual (Sirey et al., 2017). For this analysis, we examined dosing adequacy and adherence at 6 and 12 weeks as predictors of depression response in both groups at 12 and 24 weeks. SETTING: Primary care practices. PARTICIPANTS: One hundred eighty-seven older adults with depression prescribed an antidepressant for depression by their primary care provider. MEASUREMENTS: Depression response was defined as 50% reduction on the Hamilton Rating Scale for Depression. Adherence was defined as taking 80% of doses at follow-up interviews (6 and 12 weeks). Patient-reported dosage and duration of antidepressant therapy was collected using the Composite Antidepressant Score (adequacy score of >3) at follow-up. RESULTS: Greater adherence, but not receipt of adequate dosage, was associated with higher likelihood of treatment response at both 12 (Odds ratio (OR) = 2.63; 95% Confidence Interval (CI), 1.19-5.84) and 24 weeks (OR = 3.09; 95% CI, 1.46-6.55). CONCLUSION: As physicians prescribe antidepressants to the diverse group of adults seen in primary care, special attention to patients' views and approach to adherence may improve depression outcomes.