Levels of Telehealth Use, Perceived Usefulness, and Ease of Use in Behavioral Healthcare Organizations After the COVID-19 Pandemic.

The use of telehealth in behavioral healthcare increased significantly since the start of the COVID-19 pandemic and remains high even as a return to in-person care is now feasible. The use of telehealth is a promising strategy to increase access to behavioral healthcare for underserved and all populations. Identifying opportunities to improve the provision of telehealth is vital to ensuring access. An online survey about the current use of, and attitudes toward, telehealth was conducted by five Mental Health Technology Transfer Center (MHTTC) regional centers and the MHTTC Network Coordinating Office. The national MHTTC network provides training and technical assistance, to support the behavioral health workforce to implement evidence-based treatments. Three hundred and sixty-five respondents from 43 states and Puerto Rico participated. The majority of respondents were clinical providers (69.3%). Nearly all (n = 311) respondents reported providing at least one telehealth service at their organization, but the number and type of services varied substantially. Respondents had positive views of both video-based and phone-based services, but most had some preference for video-based telehealth services. Other services, including text message reminders, medication services, and mobile apps for treatment or recovery, were offered via telehealth by ~ 50% or fewer of respondents' organizations. Many organizations have areas where they could expand their telehealth use, allowing them to extend the reach of their services and increase access for populations that experience barriers to service access, though organizational barriers may still prevent this.

Differences in self-reported disruptions in mental health treatment during COVID-19 in a national household sample: impact of severity of functional impairment.

Objective: This report uses data from Mental Disorders Prevalence Study (MDPS), a large epidemiologic study that provided national prevalence estimates of seven mental disorders based on the Structured Clinical Interview for DSM-5 (SCID), to assess the odds of treatment disruption during COVID for SMI and non-SMI groups. Methods: This cross-sectional study conducted from 2020 to 2022 included 2,810 household participants with any lifetime mental health treatment. Weighted logistic regressions estimated the odds of reporting disruptions in access to mental health care or psychotropic prescriptions due to COVID. SMI was broadly defined as having an MDP diagnosis and serious functional impairment (GAF ≤50, a validated and widely used cutoff). Non-SMI groups were a mental diagnosis without serious impairment (MDPS diagnosis, GAF >50) and any lifetime treatment and no serious impairment (no MDPS diagnosis, GAF >50). Results: The SMI and mental disorder without serious impairment groups had approximately 6.4- and 2.4-greater odds, respectively, of reporting inability to access mental health care and 4- and 3- greater odds, respectively, of having prescriptions delayed, relative to the group with any lifetime treatment. Among those with serious mental illness, having Medicare insurance increased the odds of reporting inability to access mental health care. Conclusions: Individuals with SMI were much more likely to experience treatment disruptions throughout the pandemic than non-SMI groups.

Social Vulnerability and Prevalence and Treatment for Mental Health and Substance Use Disorders.

Importance: Community-level social vulnerability (SV) is associated with physical illness and premature mortality. Its association with mental health (MH) and substance use disorders (SUDs) needs further study. Objective: To study associations of SV with clinical diagnoses of MH disorders, SUDs, and related treatments in the US noninstitutionalized population of adults aged 18 years and older. Design, Setting, and Participants: A survey of adults in a national sample of US households between October 2020 and October 2022. Participants drawn from a multistage, clustered, and stratified area probability sample of US households were included, excluding adults older than 65 years because of the difficulty of differentiating mental disorders from symptoms of dementia. The sample also included adults living in prisons, state psychiatric hospitals, and homeless shelters who were excluded from the sample of US households used in these analyses. Each sample household was sent a letter explaining the study and offering the option to complete the household roster online, by phone, or by email. Of the 12 906 adults selected for clinical interviewing in the household sample, 4674 completed clinical interviews. Main Outcomes and Measures: Main outcomes were Structured Clinical Interview for DSM-5 past-year diagnoses of MH disorders and SUDs and responses to survey questions regarding treatment received. The Social Vulnerability Metric (SVM) and the Area Deprivation Index (ADI) were used to determine SV at the residential zip code level. Results: The analysis involved 4674 participants (2904 [62.13%] female and 1770 [37.87%] male; mean [SD] age, 41.51 [13.41] years). Controlling for measured confounders, the SVM was significantly associated with diagnoses of schizophrenia spectrum disorder (SSD; adjusted odds ratio [aOR], 17.22; 95% CI, 3.05-97.29), opioid use disorder (OUD; aOR, 9.47; 95% CI, 2.30-39.02), stimulant use disorder (aOR, 6.60; 95% CI, 2.01-21.67), bipolar I disorder (aOR, 2.39; 95% CI, 1.19-4.80), posttraumatic stress disorder (aOR, 1.63; 95% CI, 1.06-2.50), and any MH disorder (aOR, 1.44; 95% CI, 1.14-1.83), but not major depressive disorder (MDD), generalized anxiety disorder (GAD), or any SUD. Results were similar for the ADI but generally of lower magnitude (SSD aOR, 11.38; 95% CI, 1.61-80.58; OUD aOR, 2.05; 95% CI, 0.30-14.10; stimulant use disorder aOR, 2.18; 95% CI, 0.52-9.18). Among participants with SSDs, SV was associated with reduced MH treatment (aOR, 0.001; 95% CI, 0.00-0.18) and reduced SUD treatment in participants with OUD or stimulant use disorder (aOR, 0.24; 95% CI, 0.02-2.80). Conclusions and Relevance: In contrast to previous studies using nonclinical symptom-based survey data, we found no association between SV and GAD or MDD. By contrast, there were associations of SV with prevalence of SSD, stimulant use disorder, and OUD with corresponding decreases in treatment. These results suggest that the SVM might assist in developing more comprehensive care models that integrate medical and social care for MH disorders and SUDs.

Factors influencing diabetes treatment satisfaction in the INtegrating DEPrEssioN and Diabetes treatmENT randomized clinical trial: A multilevel model analysis.

AIMS: Patient satisfaction is associated with positive diabetes outcomes. However, there are no identified studies that evaluate both patient- and clinic-level predictors influencing diabetes care satisfaction longitudinally. METHODS: Data from the INtegrating DEPrEssioN and Diabetes treatmENT trial was used to perform the analysis. We used fixed and random effects models to assess whether and how changes in patient-level predictors (treatment assignment, depression symptom severity, systolic blood pressure, body mass index, LDL cholesterol, and haemoglobin A1C) from 0 to 24 months and clinic-level predictors (visit frequency, visit cost, number of specialists, wait time, time spent with healthcare provider, and receiving verbal reminders) measured at 24 months influence diabetes care satisfaction from 0 to 24 months. RESULTS: Model 1 (patient-level predictors) accounted for 7% of the change in diabetes satisfaction and there was a significant negative relationship between change in depressive symptoms and care satisfaction (ß = -0.23, SE = 0.12, p < 0.05). Within Model 1, 2% of the variance was explained by clinic-level predictors. Model 2 included both patient- and clinic-level predictors and accounted for 18% of the change in diabetes care satisfaction. Within Model 2, 9% of the variance was attributed to clinic-level predictors. There was also a cross-level interaction where the change in depression had less of an impact on the change in satisfaction for those who received a verbal reminder (ß = -0.11, SE = 0.21, p = 0.34) compared with those who did not receive a reminder (ß = -0.62, SE = 0.08, p < 0.01). CONCLUSIONS: Increased burden of depressive symptoms influences diabetes care satisfaction. Clinic-level predictors also significantly influence diabetes care satisfaction and can reduce dissatisfaction in primary care, specifically, reminder calls from clinic staff.

Supporting Implementation Through Online Learning Communities: Lessons Learned From a National Training and Technical Assistance Network.

Recent implementation science frameworks highlight the role of training and technical assistance (TTA) in building workforce capacity to implement evidence-based practices (EBPs). However, evaluation of TTA is limited. We describe three case examples that highlight TTA by three regional centers in the national Mental Health Technology Transfer Center (MHTTC) network. Each MHTTC formed Learning Communities (LCs) to facilitate connections among behavioral health professionals with the goals of sharing implementation strategies, discussing best-practices, and developing problem solving techniques. Data on outcomes were collected through a combination of self-report surveys and qualitative interviews. LC participants reported strong connectedness, gains in knowledge and skills, improvements in implementation capacity, and intentions to advocate for organizational and systems-level change. Furthermore, across the case examples, we identified LC characteristics that are associated with participant perceptions of outcomes, including tailoring LC content to workforce needs, providing culturally relevant information, engaging leaders, forming connections among participants and trainers, and challenging participants' current workplace practices. These findings are interpreted through the lens of the Interactive Systems Framework, which focuses on how TTA, such as LCs, can facilitate connections between the theoretical and empirical foundations of interventions and the practices of implementing interventions in real-world settings to advance workforce capacity.

Supporting psychosis research, implementation, and training through an academic intermediary-purveyor organization.

Intermediary-purveyor organizations (IPOs) are a type of dissemination support system that are intended to enhance the adoption and sustainment of empirically supported treatments (ESTs) by deploying empirically supported strategies to remediate implementation challenges. Despite the recent proliferation of government-funded IPOs for other psychiatric populations, IPOs that can redress the substantial science-to-practice gap among clients who experience psychotic disorders are not well documented. This article provides an overview of an IPO in an R1 academic medical center whose mission is to enhance access to evidence-based interventions for individuals who have or are at risk for a psychotic disorder. The article spotlights the functions of an IPO and illustrates these functions with a use case, cognitive behavioral therapy for psychosis. We highlight IPO-led activities related to cognitive behavioral therapy for psychosis purveyance, professional development, quality improvement, public awareness education and training, research and evaluation, as well as program and policy development. Finally, we address the advantages and disadvantages of establishing IPOs of this nature in academic medical centers, the importance of academic-community partnerships in advancing EST implementation, and present considerations for replication. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Association of collaborative care intervention features with depression and metabolic outcomes in the INDEPENDENT study: A mixed methods study.

AIMS: The INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) trial tested a collaborative care model including electronic clinical decision support (CDS) for treating diabetes and depression in India. We aimed to assess which features of this clinically and cost-effective intervention were associated with improvements in diabetes and depression measures. METHODS: Post-hoc analysis of the INDEPENDENT trial data (189 intervention participants) was conducted to determine each intervention feature's effect: 1. Collaborative case reviews between expert psychiatrists and the care team; 2. Patient care-coordinator contacts; and 3. Clinicians' CDS prompt modifications. Primary outcome was baseline-to-12-months improvements in diabetes control, blood pressure, cholesterol, and depression. Implementer interviews revealed barriers and facilitators of intervention success. Joint displays integrated mixed methods' results. RESULTS: High baseline HbA1c≥ 74.9 mmol/mol (9%) was associated with 5.72 fewer care-coordinator contacts than those with better baseline HbA1c (76.8 mmol/mol, 9.18%, p < 0.001). Prompt modification proportions varied from 38.3% (diabetes) to 1.3% (LDL). Interviews found that providers' and participants' visit frequencies were preference dependent. Qualitative data elucidated patient-level factors that influenced number of clinical contacts and prompt modifications explaining their lack of association with clinical outcomes. CONCLUSION: Our mixed methods approach underlines the importance of the complementarity of different intervention features. Qualitative findings further illuminate reasons for variations in fidelity from the core model.

The Impact of a Collaborative Care Model on Health Trajectories among Patients with Co-Morbid Depression and Diabetes: The INDEPENDENT Study.

Context: Collaborative care models for depression have been successful in a variety of settings, but their success may differ by patient engagement. We conducted a post-hoc analysis of the INDEPENDENT trial to investigate the role of differential engagement of participants on health outcomes over 3 years. Settings and Design: INDEPENDENT study was a parallel, single-blinded, randomised clinical trial conducted at four socio-economically diverse clinics in India. Participants were randomised to receive either active collaborative care or usual care for 12 months and followed up for 24 months. Method: We grouped intervention participants by engagement, defined as moderate (≤7 visits) or high, (8 or more visits) and compared them with usual care participants. Improvements in composite measure (depressive symptoms and at least one of three cardio-metabolic) were the primary outcome. Statistical Analysis: Mean levels of depression and cardio-metabolic measures were analysed over time using computer package IBM SPSS Statistics 25. Results: The composite outcome was sustained the highest in the moderate engagers [27.5%, 95% confidence interval (CI): 19.5, 36.7] and the lowest in high engagers (15.8%, 95% CI: 8.1, 26.8). This pattern was observed for individual parameters - depressive symptoms and glycosylated haemoglobin. Progressive reductions in mean depressive symptom scores were observed for moderate engagers and usual care group from baseline to 36 months. However, in high engagers of collaborative care, mean depressive symptoms were higher at 36 months compared to 12 months. Conclusion: Sustained benefits of collaborative care were larger in participants with moderate engagement compared with high engagement, although a majority of participants relapsed on one or more outcome measures by 36 months. High engagers of collaborative care for co-morbid depression and diabetes may need light touch interventions for longer periods to maintain health and reduce depressive symptoms.

Adaptation of the collaborative care model to integrate behavioral health care into a low-barrier HIV clinic.

Background: The collaborative care management (CoCM) model is an evidence-based intervention for integrating behavioral health care into nonpsychiatric settings. CoCM has been extensively studied in primary care clinics, but implementation in nonconventional clinics, such as those tailored to provide care for high-need, complex patients, has not been well described. Method: We adapted CoCM for a low-barrier HIV clinic that provides walk-in medical care for a patient population with high levels of mental illness, substance use, and housing instability. The Exploration, Preparation, Implementation, and Sustainment model guided implementation activities and support through the phases of implementing CoCM. The Framework for Reporting Adaptations and Modifications to Evidence-Based Interventions guided our documentation of adaptations to process-of-care elements and structural elements of CoCM. We used a multicomponent strategy to implement the adapted CoCM model. In this article, we describe our experience through the first 6 months of implementation. Results: The key contextual factors necessitating adaptation of the CoCM model were the clinic team structure, lack of scheduled appointments, high complexity of the patient population, and time constraints with competing priorities for patient care, all of which required substantial flexibility in the model. The process-of-care elements were adapted to improve the fit of the intervention with the context, but the core structural elements of CoCM were maintained. Conclusions: The CoCM model can be adapted for a setting that requires more flexibility than the usual primary care clinic while maintaining the core elements of the intervention.

What is already known about this topic? Collaborative care management is an evidence-based intervention to integrate behavioral health care into primary medical care. The model uses a task-sharing approach in which a behavioral health care manager who is supervised by a remote psychiatrist works with the primary medical team. What does this paper add? We describe adaptation of the collaborative care management model for a low-barrier HIV care clinic. Adaptation was necessary because the clinic provides all care on a walk-in basis, the team structure differs from usual primary care, and the patient population has complex medical and social needs. What are the implications for practice, research or policy? Our experience can inform implementation of collaborative care management into other medical settings that are designed to provide care for high-need, complex patient populations.

Successful ingredients of effective Collaborative Care programs in low- and middle-income countries: A rapid review.

Integrating mental health care in primary healthcare settings is a compelling strategy to address the mental health treatment gap in low- and middle-income countries (LMICs). Collaborative Care is the integrated care model with the most evidence supporting its effectiveness, but most research has been conducted in high-income countries. Efforts to implement this complex multi-component model at scale in LMICs will be enhanced by understanding the model components that have been effective in LMIC settings. Following Cochrane Rapid Reviews Methods Group recommendations, we conducted a rapid review to identify studies of the effectiveness of Collaborative Care for priority adult mental disorders of mhGAP (mood and anxiety disorders, psychosis, substance use disorders and epilepsy) in outpatient medical settings in LMICs. Article screening and data extraction were performed using Covidence software. Data extraction by two authors utilized a checklist of key components of effective interventions. Information was aggregated to examine how frequently the components were applied. Our search yielded 25 articles describing 20 Collaborative Care models that treated depression, anxiety, schizophrenia, alcohol use disorder or epilepsy in nine different LMICs. Fourteen of these models demonstrated statistically significantly improved clinical outcomes compared to comparison groups. Successful models shared key structural and process-of-care elements: a multi-disciplinary care team with structured communication; standardized protocols for evidence-based treatments; systematic identification of mental disorders, and a stepped-care approach to treatment intensification. There was substantial heterogeneity across studies with respect to the specifics of model components, and clear evidence of the importance of tailoring the model to the local context. This review provides evidence that Collaborative Care is effective across a range of mental disorders in LMICs. More work is needed to demonstrate population-level and longer-term outcomes, and to identify strategies that will support successful and sustained implementation in routine clinical settings.

Adapting a transdiagnostic digital mental health intervention for use among immigrant and refugee youth in Seattle: a human-centered design approach.

Digital mental health interventions show promise in addressing mental health needs, especially among youth and marginalized communities. This study adapted the World Health Organization -developed STARS (Sustainable Technology for Adolescents to Reduce Stress) digital mental health intervention for use among youth and young adults aged 14-25 from immigrant and refugee communities in Seattle, Washington. Human-centered design methods centered around qualitative semi-structured interviews were used to contextually and culturally adapt the intervention and prioritize the needs and preferences of the intended end user. Intervention prototypes were modified and then presented to the target groups in iterative cycles until saturation was achieved. Qualitative interviews occurred in three iterations of five participants each. Modifications were documented according to the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) implementation science framework. Modifications aligned with the FRAME process elements: (a) tailoring/refining, which included adapting language to less resemble digital phishing scams; (b) changes in packaging or materials, which included naming the chatbot and adopting a corresponding avatar; (c) adding/removing, which included changing existing emojis and adding additional media types including graphics interchange format images, pictures, and voice memos; (d) shortening/condensing, which included shortening the length of individual text sections as well as deleting redundant language; (e) lengthening/extending, which included allowing the user to choose to receive content catered to teenagers or to adults; and (f) loosening structure, including giving users options to skip parts of modules or to engage with additional material. The modified STARS intervention shows promise for engagement with immigrant and refugee youth in Seattle and can be examined for clinical effectiveness. Adaptations increased the relevance of content to the intended end user, expanded options for personalization and customization of the user experience, and utilized language that was age appropriate, engaging, and did not invoke feelings of stigma or distrust. Adaptations of digital mental health interventions should focus on modifications that maximize acceptability and appropriateness to intended audiences.

Digital mental health interventions like apps and online mental health tools show promise in addressing mental health needs. This study adapted the STARS (Sustainable Technology for Adolescents to Reduce Stress) digital mental health intervention for use among youth and young adults from immigrant and refugee communities in Seattle, Washington. In our study, we adapted the intervention in a way that prioritizes the preferences of the intended end user. Modifications occurred in cycles: each time modifications resulted in a new version, the version was presented to a group of participants for their feedback and further modifications. Modifications in the final version included adapting language to less resemble digital phishing scams; naming the chatbot and adopting a corresponding avatar; changing existing emojis and adding additional media types; shortening the length of individual text sections as well as deleting redundant language; allowing the user to choose content catered to teenagers or to adults; and giving users options to skip parts of modules or to engage with additional material. The modified STARS intervention shows promise for engagement with immigrant and refugee youth in Seattle and can be examined for clinical effectiveness.

Substance Use and Mental Health Comorbidities and Receipt of Specialty Care Among Patients Enrolled in a Low-Barrier HIV Clinic.

Low-barrier care is one model of a differentiated service delivery approach for people with HIV (PWH) who are not engaged in conventionally-organized HIV care. Although psychiatric and substance use disorders are common among patients in low-barrier clinics, approaches to behavioral health service delivery within this context have not been well-described. We conducted a descriptive analysis using retrospective review of medical records to evaluate substance use and psychiatric comorbidities and receipt of behavioral health services among patients in the Max Clinic in Seattle, Washington. Among 227 patients enrolled from 2015 to mid-2020, most had a history of hazardous substance use (85%), a psychiatric diagnosis (69%) or unstable housing (69%) documented in the medical record. Less than half of patients referred for depression treatment (33%) or for opioid use disorder treatment (40%) completed even one specialty care visit. More effective approaches are needed to engage patients in behavioral health services within the context of low-barrier HIV care.

Development and Pilot Testing of a Nurse Care Manager Role in Coordinated Specialty Care for Early Psychosis.

Coordinated specialty care (CSC) improves mental health and functional outcomes among individuals with first-episode psychosis but lacks a standardized approach to addressing chronic disease risk. The authors used community-based participatory intervention mapping with nine CSC teams to implement a nurse care manager role for the team in order to identify and address chronic disease risk factors. The role was piloted at one CSC site to explore its feasibility and acceptability. The nurse care manager role was highly acceptable to clients, team members, and leadership. More than one-quarter of the nurse's time was spent on nonbillable activities, and lack of a clear plan for financial sustainability was the primary barrier to implementation.

Long-term Effects of a Collaborative Care Model on Metabolic Outcomes and Depressive Symptoms: 36-Month Outcomes from the INDEPENDENT Intervention.

BACKGROUND: Collaborative care (CC) is a multicomponent team-based approach to providing mental health care with systematic integration into outpatient medical settings. The 12-month INDEPENDENT CC intervention improved joint disease control measures in patients with both depression and diabetes at 12 and 24 months following randomization. OBJECTIVE: This study investigated the durability of intervention effects on patient outcomes at 36 months following randomization. PARTICIPANTS: Adult patients with poorly controlled T2D and depression in India randomized to CC or usual care. DESIGN: Post hoc analyses of between-group differences in patient outcomes at 36 months post-randomization (N = 331) and maintenance of outcomes from 12 to 36 months (N = 314). MAIN MEASURES: We evaluated combined risk factor improvement since baseline, defined as ≥ 50.0% reduction in Symptom Checklist Depression Scale (SCL-20) scores along with reduction of at least 0.5 percentage point hemoglobin A1C, 5 mmHg systolic blood pressure, or 10 mg/dL low-density lipoprotein cholesterol. Improvements in single risk factors were also examined. KEY RESULTS: There were no between-group differences in improvements since baseline in multiple or single risk factors at 36 months. Patients in the CC group with improved outcomes at 12 months were more likely to maintain a ≥ 50.0% reduction since baseline in SCL-20 scores (CC [54.9%] vs. UC [40.9%]; RR: 1.27 [95% CI: 1.04, 1.56]) and 0.5 percentage point reduction since baseline in hemoglobin A1C (CC [31.9%] vs. UC [19.5%]; RR: 1.64 [95% CI: 1.11, 2.41]) at 36 months. CONCLUSIONS: While improvements since baseline in patient outcomes did not differ between the collaborative care and usual care groups at 36 months, patients who received CC were more likely to maintain improvements in depressive symptoms and glucose levels at 36 months if they had achieved these improvements at the end of active intervention. TRIAL REGISTRATION NUMBER: NCT02022111.

Cost-Effectiveness of a Collaborative Care Model Among Patients With Type 2 Diabetes and Depression in India.

OBJECTIVE: To assess the cost-effectiveness of collaborative versus usual care in adults with poorly controlled type 2 diabetes and depression in India. RESEARCH DESIGN AND METHODS: We performed a within-trial cost-effectiveness analysis of a 24-month parallel, open-label, pragmatic randomized clinical trial at four urban clinics in India from multipayer and societal perspectives. The trial randomly assigned 404 patients with poorly controlled type 2 diabetes (HbA1c ≥8.0%, systolic blood pressure ≥140 mmHg, or LDL cholesterol ≥130 mg/dL) and depressive symptoms (9-item Patient Health Questionnaire score ≥10) to collaborative care (support from nonphysician care coordinators, electronic registers, and specialist-supported case review) for 12 months, followed by 12 months of usual care or 24 months of usual care. We calculated incremental cost-effectiveness ratios (ICERs) in Indian rupees (INR) and international dollars (Int'l-$) and the probability of cost-effectiveness using quality-adjusted life-years (QALYs) and depression-free days (DFDs). RESULTS: From a multipayer perspective, collaborative care costed an additional INR309,558 (Int'l-$15,344) per QALY and an additional INR290.2 (Int'l-$14.4) per DFD gained compared with usual care. The probability of cost-effectiveness was 56.4% using a willingness to pay of INR336,000 (Int'l-$16,654) per QALY (approximately three times per-capita gross domestic product). The willingness to pay per DFD to achieve a probability of cost-effectiveness >95% was INR401.6 (Int'l-$19.9). From a societal perspective, cost-effectiveness was marginally lower. In sensitivity analyses, integrating collaborative care in clinical workflows reduced incremental costs by ∼47% (ICER 162,689 per QALY, cost-effectiveness probability 89.4%), but cost-effectiveness decreased when adjusting for baseline values. CONCLUSIONS: Collaborative care for patients with type 2 diabetes and depression in urban India can be cost-effective, especially when integrated in clinical workflows. Long-term cost-effectiveness might be more favorable. Scalability across lower- and middle-income country settings depends on heterogeneous contextual factors.

A realist process evaluation of the INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) randomized controlled trial in India.

Aims: We aimed to determine what key resources, mechanisms, and contextual factors are necessary to integrate depression and diabetes treatment into low-resource settings. Methods: A realist evaluation framework was employed to conduct a comparative case study. Data were collected through document review, key informant interviews (n = 4), activity logs, and interviews with implementing health care providers (n = 11) to test and refine program theories for collaborative care. Results: Efforts to enhance patient care coordination (i.e., adapting clinics' patient flow and resources, on-going trainings, and on-site support for care coordinators) improved implementation of depression treatment by usual care diabetes physicians. Clinician's avoidance of the term depression was identified as a barrier to mental health counseling and treatment. Conclusions: The variations in organizational features and processes linked to implementation activities across two clinics provided an opportunity to examine how and why different contextual factors help or hinder the implementation process. Findings from this study demonstrate that successful implementation of an integrated depression and diabetes care model is feasible in a low-resource setting, while the revised program theories provide an explanatory framework of coordinated care implementation processes that can inform future efforts to disseminate and scale this care model.

Developing the Workforce of the Digital Future: Leveraging Technology to Train Community-Based Mobile Mental Health Specialists.

Challenges in training, dissemination, and implementation have impeded the ability of providers to integrate promising digital health tools in real-world services. There is a need for generalizable strategies to rapidly train real-world providers at scale to support the adoption of digital health. This study describes the development of principles guiding rapid training of community-based clinicians in the support of digital health. This training approach was developed in the context of an ongoing trial examining implementation strategies for FOCUS, a mobile mental health intervention designed for people with serious mental illness. The SAIL (Simple, Accessible, Inverted, Live) model introduces how digital tools can be leveraged to facilitate rapid training of community agency-based personnel to serve as digital mental health champions, promoters, and providers. This model emphasizes simple and flexible principles of intervention delivery, accessible materials in a virtual learning environment, inverted or "flipped" live training structure, and live consultation calls for ongoing support. These initial insights lay the groundwork for future work to test and replicate generalizable training strategies focused on real-world delivery of digital mental health services. These strategies have the potential to remove key obstacles to the implementation and dissemination of digital health interventions for mental health.

The relationship among social support, food insecurity and mental health for adults with severe mental illness and type 2 diabetes: A survey study.

OBJECTIVE: People living with severe mental illness are at increased risk of medical comorbidity as well as poverty, food insecurity, and inadequate social support in managing their mental and physical health conditions. Lack of access to sufficient food negatively affects a person's ability to manage health conditions, in particular diabetes, which is twice as common among people with severe mental illness as the general population. This study aimed to explore associations among food insecurity, social support, and psychiatric symptoms among adults with severe mental illness and diabetes. METHOD: A cross-sectional survey was conducted between January and May 2021 among adults (N = 156) with severe mental illness and type 2 diabetes who received primary care through a large academic health-care system (26% response rate). Valid and reliable questionnaires were implemented to measure food insecurity, social support, and mental health. Regression analysis was applied to examine the associations between food security status, social support, and mental health. RESULTS: Food insecurity and social support are both correlated with psychiatric symptom severity. Specifically, support from family members has the largest protective role against food insecurity. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: This study found food insecurity is likely a critical issue to address whenever it is present in adults with severe mental illness (SMI) and type 2 diabetes. The presence of family support mitigates the need for addressing food insecurity. Practices and policies aimed at both addressing health inequities such as food insecurity and strengthening family support among people living with SMI and comorbid medical conditions are important adjuncts to self-management interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Development and Implementation of an Integrated Care Fellowship.

BACKGROUND: Integrated care is a common approach to leverage scarce psychiatric resources to deliver mental health care in primary care settings. OBJECTIVE: Describe a formal clinical fellowship devoted to professional development for the integrated care psychiatrist role. METHODS: The development of a formal year-long clinical fellowship in integrated care is described. The curriculum consists of an Integrated Care Didactic Series, Integrated Care Clinical Skill Experiences, and Integrated Care System-Based Leadership Experiences. Evaluation of impact was assessed with descriptive statistics. RESULTS: We successfully recruited 3 classes of fellows to the Integrated Care Fellowship, with 5 program graduates in the first 3 years. All 5 graduated fellows were hired into integrated care and/or telepsychiatry positions. Integrated Care fellows had a high participation rate in didactics (mean attendance = 80.6%; n = 5). We received a total of 582 didactic evaluations for the 151 didactic sessions. On a scale of 1 (poor) to 6 (fantastic), the mean quality of the interactive learning experience was rated as 5.33 (n = 581) and the mean quality of the talk was 5.35 (n = 582). Rotations were rated with the mean overall teaching quality of 4.98/5 (n = 76 evaluations from 5 fellows). CONCLUSIONS: The Integrated Care clinical fellowship serves as a model for training programs seeking to provide training in clinical and systems-based skills needed for practicing integrated care. Whether such training is undertaken as a standalone fellowship or incorporated into existing consultation-liaison psychiatry programs, such skills are increasingly valuable as integrated care becomes commonplace in practice.