Measuring The Lifetime Costs Of Serious Mental Illness And The Mitigating Effects Of Educational Attainment

Occupational differences in the effects of retirement on hospitalizations for mental illness among female workers: Evidence from administrative data in China

Retirement, a major transition in the life course, may affect many aspects of retirees' well-being, including health and health care utilization. Leveraging differential statutory retirement age (SRA) by occupation for China's urban female workers, we provide some of the first evidence on the causal effect of retirement on hospitalizations attributable to mental illness and its heterogeneity. To address endogeneity in retirement decisions, we take advantage of exogeneity of the differing SRA cut-offs for blue-collar (age 50) and white-collar (age 55) female urban employees. We apply a Fuzzy Regression Discontinuity Design (RDD) around the SRA cut-offs using nationally representative hospital inpatient claims data that cover these workers. We show that blue-collar females incur more hospitalizations for mental illness after retirement, while no similar change is found for white-collar females. Conditional on blue-collar females being hospitalized, probabilities of overall and ER admissions due to mental illness increase by 2.3 and 1.2 percentage points upon retirement, respectively. The effects are primarily driven by patients within the categories of schizophrenia, schizotypal and delusional disorders; and neurotic, stress-related and somatoform disorders. Moreover, the 'Donut' RDD estimates suggest that pent-up demand at retirement unlikely dominates our findings for blue-collar females. Rather, our results lend support to their worsening mental health at retirement. These findings suggest that occupational differences in mental illness and related health care utilization at retirement should be considered when optimizing retirement policy schemes.

Microsimulation Models on Mental Health: A Critical Review of the Literature

OBJECTIVES

To retrieve and synthesize the literature on existing mental health-specific microsimulation models or generic microsimulation models used to examine mental health, and to critically appraise them.

METHODS

All studies on microsimulation and mental health published in English in MEDLINE, Embase, PsycINFO, and EconLit between January 1, 2010, and September 30, 2022, were considered. Snowballing, Google searches, and searches on specific journal websites were also undertaken. Data extraction was done on all studies retrieved and the reporting quality of each model was assessed using the Quality Assessment Reporting for Microsimulation Models checklist, a checklist developed by the research team. A narrative synthesis approach was used to synthesize the evidence.

RESULTS

Among 227 potential hits, 19 studies were found to be relevant. Some studies covered existing economic-demographic models, which included a component on mental health and were used to answer mental-health-related research questions. Other studies were focused solely on mental health and included models that were developed to examine the impact of specific policies or interventions on specific mental disorders or both. Most models examined were of medium quality. The main limitations included the use of model inputs based on self-reported and/or cross-sectional data, small and/or nonrepresentative samples and simplifying assumptions, and lack of model validation.

CONCLUSIONS

This review found few high-quality microsimulation models on mental health. Microsimulation models developed specifically to examine mental health are important to guide healthcare delivery and service planning. Future research should focus on developing high-quality mental health-specific microsimulation models with wide applicability and multiple functionalities.

Psychotropic Drug-Related Weight Gain and Its Treatment

Psychotropic drug-related weight gain (PDWG) is a common occurrence and is highly associated with non-initiation, discontinuation, and dissatisfaction with psychiatric drugs. Moreover, PDWG intersects with the elevated risk for obesity and associated morbidity that has been amply reported in the psychiatric population. Evidence indicates that differential liability for PDWG exists for antipsychotics, antidepressants, and anticonvulsants. During the past two decades, agents within these classes have become available with significantly lower or no liability for PDWG and as such should be prioritized. Although lithium is associated with weight gain, the overall extent of weight gain is significantly lower than previously estimated. The benefit of lifestyle and behavioral modification for obesity and/or PDWG in psychiatric populations is established, with effectiveness similar to that in the general population. Metformin is the most studied pharmacological treatment in the prevention and treatment of PDWG, and promising data are emerging for glucagon-like peptide-1 (GLP-1) receptor agonists (e.g., liraglutide, exenatide, semaglutide). Most pharmacologic antidotes for PDWG are supported with low-confidence data (e.g., topiramate, histamine-2 receptor antagonists). Future vistas for pharmacologic treatment for PDWG include large, adequately controlled studies with GLP-1 receptor agonists and possibly GLP-1/glucose-dependent insulinotropic polypeptide co-agonists (e.g., tirzepatide) as well as specific dietary modifications.

The PSY-SIM Model: Using Real-World Data to Inform Health Care Policy for Individuals With Chronic Psychotic Disorders

BACKGROUND AND HYPOTHESIS

Few microsimulation models have been developed for chronic psychotic disorders, severe and disabling mental disorders associated with poor medical and psychiatric outcomes, and high costs of care. The objective of this work was to develop a microsimulation model for individuals with chronic psychotic disorders and to use the model to examine the impact of a smoking cessation initiative on patient outcomes.

STUDY DESIGN

Using health records and survey data from Ontario, Canada, the PSY-SIM model was developed to simulate health and cost outcomes of individuals with chronic psychotic disorders. The model was then used to examine the impact of the Smoking Treatment for Ontario Patients (STOP) program from Ontario on the development of chronic conditions, life expectancy, quality of life, and lifetime health care costs.

STUDY RESULTS

Individuals with chronic psychotic disorders had a lifetime risk of 63% for congestive heart failure and roughly 50% for respiratory disease, cancer and diabetes, and a life expectancy of 76 years. The model suggests the STOP program can reduce morbidity and lead to survival and quality of life gains with modest increases in health care costs. At a long-term quit rate of 4.4%, the incremental cost-effectiveness ratio of the STOP program was $41,936/QALY compared with status quo.

CONCLUSIONS

Smoking cessation initiatives among individuals with chronic psychotic disorders can be cost-effective. These findings will be relevant for decision-makers and clinicians looking to improving health outcomes among this patient population.

The Effects of a Digital, Transdiagnostic, Clinically and Peer-Moderated Treatment Platform for Young People With Emerging Mental Health Complaints: Repeated Measures Within-Subjects Study

BACKGROUND

To address the growing prevalence of youth mental health problems, early intervention is crucial to minimize individual, societal, and economic impacts. Indicative prevention aims to target emerging mental health complaints before the onset of a full-blown disorder. When intervening at this early stage, individuals are more responsive to treatment, resulting in cost-effective outcomes. The Moderated Online Social Therapy platform, which was successfully implemented and proven effective in Australia, is a digital, peer- and clinically moderated treatment platform designed for young people. The Netherlands was the first country outside Australia to implement this platform, under the name Engage Young People Early (ENYOY). It has the potential to reduce the likelihood of young people developing serious mental health disorders.

OBJECTIVE

This study aims to investigate the effects on young people using the ENYOY-platform in relation to psychological distress, psychosocial functioning, and positive health parameters.

METHODS

Dutch-speaking young people with emerging mental health complaints (N=131) participated in the ENYOY-platform for 6 months in a repeated measures within-subjects study. Psychological distress, psychosocial functioning, and positive health parameters were assessed at baseline and 3, 6, and 12 months. Repeated measures ANOVA was conducted and adjusted for age, sex, therapy, and community activity. The Reliable Change Index and Clinically Significant Index were computed to compare the baseline with the 6- and 12-month measurements. The missing data rate was 22.54% and the dropout rate 62.6% (82/131).

RESULTS

The primary analysis (77/131, 58.8%) showed that psychological distress decreased and psychosocial functioning improved over time with large effect sizes (P<.001 in both cases; ηp2=0.239 and 0.318, respectively) independent of age (P=.76 for psychological distress and P=.48 for psychosocial functioning), sex (P=.24 and P=.88, respectively), therapy activity (P=.49 and P=.80, respectively), or community activity (P=.59 and P=.48, respectively). Similarly, secondary analyses (51/131, 38.9%) showed significant effects of time on the quality of life, well-being, and meaningfulness positive health parameters (P<.05; ηp2=0.062, 0.140, and 0.121, respectively). Improvements in all outcome measures were found between baseline and 3 and 6 months (P≤.001-.01; d=0.23-0.62) and sustained at follow-up (P=.18-.97; d=0.01-0.16). The Reliable Change Index indicated psychological distress improvements in 38% (39/102) of cases, no change in 54.9% (56/102) of cases, and worsening in 5.9% (6/102) of cases. Regarding psychosocial functioning, the percentages were 50% (51/102), 43.1% (44/102), and 6.9% (7/102), respectively. The Clinically Significant Index demonstrated clinically significant changes in 75.5% (77/102) of cases for distress and 89.2% (91/102) for functioning.

CONCLUSIONS

This trial demonstrated that the ENYOY-platform holds promise as a transdiagnostic intervention for addressing emerging mental health complaints among young people in the Netherlands and laid the groundwork for further clinical research. It would be of great relevance to expand the population on and service delivery of the platform.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12888-021-03315-x.

The role of the dually certified primary care/psychiatric mental health nurse practitioner in treating high-needs/high-cost patients

ABSTRACT

National nursing organizations have called for nurses to provide leadership in care solutions for high-cost/high-needs vulnerable populations. In response to this call, important modifications are emerging in Doctor of Nursing Practice programs, including an increasing number of nurses pursuing dual certification in primary care and psychiatric mental health or primary care nurse practitioners returning for a postgraduate certificate in psychiatric mental health. This innovative role warrants examination, particularly because it relates to high-needs/high-cost patients such as those with serious mental illness (SMI). This article highlights two aspects of the role of the primary care/psychiatric mental health nurse practitioner (PC/PMHNP): one, to provide a vision of the PC/PMHNP as a unique solution for optimal care of vulnerable patients and two, to demonstrate potential contributions of the PC/PMHNP to the larger health care system. A case exemplar is used to illustrate role contributions of the PC/PMHNP in a high-needs/high-cost patient with SMI and complex co-occurring physical illness. Three capacities of the PC/PMHNP are discussed: depth and breath, expert engagement and rapport building, and full patient-centered care and flexibility. The case exemplar emphasizes the PC/PMHNP value through transitions across care settings and where gaps in service frequently occur. The impact of the PC/PMHNP on improved patient outcomes, patient and provider satisfaction, and cost savings are explored.

Clinician and Patient Perspectives on the Use of Passive Mobile Monitoring and Self-Tracking for Patients With Serious Mental Illness: User-Centered Approach

BACKGROUND

Early intervention in mental health crises can prevent negative outcomes. A promising new direction is remote mental health monitoring using smartphone technology to passively collect data from individuals to rapidly detect the worsening of serious mental illness (SMI). This technology may benefit patients with SMI, but little is known about health IT acceptability among this population or their mental health clinicians.

OBJECTIVE

We used the Health Information Technology Acceptability Model to analyze the acceptability and usability of passive mobile monitoring and self-tracking among patients with serious mental illness and their mental health clinicians.

METHODS

Data collection took place between December 2020 and June 2021 in 1 Veterans Administration health care system. Interviews with mental health clinicians (n=16) assessed the acceptability of mobile sensing, its usefulness as a tool to improve clinical assessment and care, and recommendations for program refinements. Focus groups with patients with SMI (n=3 groups) and individual usability tests (n=8) elucidated patient attitudes about engaging in health IT and perceptions of its usefulness as a tool for self-tracking and improving mental health assessments.

RESULTS

Clinicians discussed the utility of web-based data dashboards to monitor patients with SMI health behaviors and receiving alerts about their worsening health. Potential benefits included improving clinical care, capturing behaviors patients do not self-report, watching trends, and receiving alerts. Clinicians' concerns included increased workloads tied to dashboard data review, lack of experience using health IT in clinical care, and how SMI patients' associated paranoia and financial instability would impact patient uptake. Despite concerns, all mental health clinicians stated that they would recommend it. Almost all patients with SMI were receptive to using smartphone dashboards for self-monitoring and having behavioral change alerts sent to their mental health clinicians. They found the mobile app easy to navigate and dashboards easy to find and understand. Patient concerns centered on privacy and "government tracking," and their phone's battery life and data plans. Despite concerns, most reported that they would use it.

CONCLUSIONS

Many people with SMI would like to have mobile informatics tools that can support their illness and recovery. Similar to other populations (eg, older adults, people experiencing homelessness) this population presents challenges to adoption and implementation. Health care organizations will need to provide resources to address these and support successful illness management. Clinicians are supportive of technological approaches, with adapting informatics data into their workflow as the primary challenge. Despite clear challenges, technological developments are increasingly designed to be acceptable to patients. The research development-clinical deployment gap must be addressed by health care systems, similar to computerized cognitive training. It will ensure clinicians operate at the top of their skill set and are not overwhelmed by administrative tasks, data summarization, or reviewing data that do not indicate a need for intervention.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/39010.

Prevalence, risk factors and multiple outcomes of treatment delay in Chinese patients with schizophrenia

BACKGROUND

People with schizophrenia often delay treatment. This issue is not fully understood, particularly in low-and middle-income countries. This study aimed to elucidate the prevalence, risk factors and multiple outcomes of treatment delay in schizophrenia in a Chinese metropolis.

METHODS

A two-stage whole cluster sampling survey was conducted in Beijing, China in 2020. A total of 1,619 patients with schizophrenia were included. Heterogeneity between groups and the changing trend of treatment delay were presented. Regression modelling methods were used to examine both the risk factors for treatment delay and related outcomes at individual and family levels.

RESULTS

The median treatment delay for schizophrenia was 89 days (about 13 weeks). 49.35% surveyed patients delayed treatment for more than three months. Early age of onset, low level of education, living in well developed districts were important risk factors. Treatment delay in schizophrenia was significantly associated with patients' poor medication adherence, comorbidity status and poor social functioning. It also increased the negative impact of the illness on families.

CONCLUSIONS

This study accumulated evidence of treatment delay in schizophrenia in China. It occurs even in the metropolis where mental health resources are relatively adequate. Further targeted interventions to raise public awareness should be crucial to reduce treatment delay.

Codesigning a user-centred digital psychoeducational tool for youth mental well-being with families in Canada: study protocol for a sequential exploratory mixed methods study

INTRODUCTION

On 11 March 2020, WHO declared the novel coronavirus (COVID-19) disease a global pandemic. Governments globally implemented physical distancing measures and closure of public institutions that resulted in varying implications to youth mental well-being (eg, social isolation, reduced extracurricular activities). These impacts may have detrimental short-term and long-term effects on youth mental well-being; care for youth with mental health disorders was already overstretched, underfunded and fragmented before the pandemic and youth are not often considered in mental health initiatives. There is a pressing need to partner with youth and families to target and improve youth mental well-being prior to the onset of a mental health disorder, as well as to conduct research on youth mental well-being needs related to pandemic recovery. Here we present a protocol for partnering with youth and families to codesign a user-centred digital tool for youth mental well-being.

METHODS AND ANALYSIS

We will conduct a national research study to develop a catalogue of recommendations specific to supporting youth mental well-being, and a digital tool to support youth mental well-being through three phases of work: (1) expert consultation on data related to supporting youth mental well-being existing within our Pandemic Preparedness Research Program; (2) codesign of an innovative digital tool for youth mental well-being; and (3) assessment of the tool's usability and acceptability.

ETHICS AND DISSEMINATION

This study has been approved by the Dalhousie Research Ethics Board (2023-6538) and the Conjoint Health Research Ethics Board (23-0039). This study will complement ongoing foundational research in youth conducted by our team that involves partnering with youth and families to understand the unique implications of the pandemic on this population.

Analysis of Educational Attainment in a Mexican Psychiatric Patient Population with Bipolar or Psychotic Disorders

Schizophrenia has been associated with premorbid poor educational performance and low educational attainment (EA). However, some studies have found positive associations between psychotic disorders and excellent scholastic performance. In the present study, we examined the association between EA and several clinical and nonclinical characteristics in psychiatric patients diagnosed with psychotic or bipolar disorders. Data were obtained from the files of 1132 patients who entered a major Mexico City psychiatric hospital during the years 2009-2010 for the treatment of psychotic symptoms and who were subsequently diagnosed with schizophrenia, bipolar, schizoaffective, or another psychotic disorder. Chi-squared tests, t-tests, and Cox regression analysis were applied to explore associations between EA and factors including gender, familial history of mental illness, premorbid personality characteristics, age of symptom onset, diagnosis, civil status, and current employment. Family history of mental illness decreased the hazard of having lower EA (B = -0.137, p = 0.025, ExpB = 0.872, 95% CI = 0.774-0.983), while a schizophrenia diagnosis independently increased it (B = 0.201, p = 0.004, ExpB = 1.223, 95% CI = 1.068-1.401). In male patients (but not in females), family history of mental illness was significantly associated with higher EA, while in female patients, premorbid schizoid-like personality characteristics were associated with lower EA. For both genders, lower EA was associated with having more children and being employed in manual labor, while higher EA was associated with professional employment. Conclusions: Compared with bipolar disorder, a schizophrenia diagnosis is associated with lower EA; however, familial history of mental illness and premorbid schizoid-like characteristics independently favor higher and lower EA in males and females, respectively. Since lower EA is generally associated with a lower economic status, special preventative attention should be given to students at high risk for schizophrenia, particularly those displaying a schizoid-like personality.

Incidence of mental disorders in the general population aged 1-30 years disaggregated by gender and socioeconomic status

PURPOSE

The objective of this study was to estimate the incidence and age of onset of mental disorders diagnosed by gender and socioeconomic status (SES) in children, adolescents, and young adults up to 30 years of age in the whole population of the Basque Country (Spain).

METHODS

All mental health diagnoses documented in Basque Health Service records from 1 January 2003 to 31 December 2018, were classified into eight clusters: anxiety, attention deficit hyperactivity disorder (ADHD), conduct disorders, depression, psychosis/personality disorders, substance use, eating disorders, and self-harm. We calculated incidence and cumulative incidence for each cluster, disaggregated by gender, and socioeconomic status (SES). Poisson regression analyses were performed.

RESULTS

Overall, 9,486,853 person-years of observation were available for the 609,281 individuals included. ADHD and conduct disorders were diagnosed in the first decade, anxiety and depression disorders in the second and third decades, and psychosis/personality and substance use in the third. The cumulative incidence at 18 years of age for any type of disorder was 15.5%. The group with low SES had a statistically significantly higher incidence of all eight clusters. The incidence of ADHD, conduct disorders, depression, psychosis/personality disorders, and substance use was higher in males and that of anxiety, eating disorders and self-harm was higher in females.

CONCLUSIONS

The incidence of mental disorders is high among children, adolescents, and young adults in the Basque Country underlining the need for preventive interventions. Marked differences by gender and SES highlight mental health inequalities, especially for depression and psychosis in low SES males.

Suicide rates among people with serious mental illness: a systematic review and meta-analysis

BACKGROUND

People with serious mental illness are at great risk of suicide, but little is known about the suicide rates among this population. We aimed to quantify the suicide rates among people with serious mental illness (bipolar disorder, major depression, or schizophrenia).

METHODS

PubMed and Web of Science were searched to identify studies published from 1 January 1975 to 10 December 2020. We assessed English-language studies for the suicide rates among people with serious mental illness. Random-effects meta-analysis was used. Changes in follow-up time and the suicide rates were presented by a locally weighted scatter-plot smoothing (LOESS) curve. Suicide rate ratio was estimated for assessments of difference in suicide rate by sex.

RESULTS

Of 5014 identified studies, 41 were included in this analysis. The pooled suicide rate was 312.8 per 100 000 person-years (95% CI 230.3-406.8). Europe was reported to have the highest pooled suicide rate of 335.2 per 100 000 person-years (95% CI 261.5-417.6). Major depression had the highest suicide rate of 534.3 per 100 000 person-years (95% CI 30.4-1448.7). There is a downward trend in suicide rate estimates over follow-up time. Excess risk of suicide in males was found [1.90 (95% CI 1.60-2.25)]. The most common suicide method was poisoning [21.9 per 100 000 person-years (95% CI 3.7-50.4)].

CONCLUSIONS

The suicide rates among people with serious mental illness were high, highlighting the requirements for increasing psychological assessment and monitoring. Further study should focus on region and age differences in suicide among this population.

A digital patient-reported outcome (electronic patient-reported outcome) system for patients with severe psychiatric disorders: User-centered development study and study protocol of a multicenter-controlled trial

Background

The effective treatment of patients with severe psychiatric disorders primarily relies on subjective reporting of symptoms and side-effects. This information is crucial for a clinician's decision regarding medication adjustment. Treatment adjustment usually happens at a low frequency (∼4-8 weeks). In between points of care, patients are left alone with their symptoms and side-effects. This leads to uncertainty regarding the treatment, non-adherence, possible relapse, and rehospitalization.

Objectives

We aim to design a flexible electronic patient-reported outcome (ePRO) system, which allows patients with severe psychiatric disorders to: (a) record their symptoms using an app; (b) share the data with the clinical team at points of care; and (c) utilize the data to support therapy decisions.

Methods

In this article, we describe the development process which included the following steps: (a) formation of a co-design team; (b) stakeholder interviews with patients, practitioners, and digital health experts to access needs, requirements, and barriers; (c) prototype conceptualization and design; (d) user acceptance testing and refinement; and (e) finalization of the system for testing in a pilottrial.

Results

We included input from patients with lived experience of psychiatric disorders, clinical team members, software engineers, and researchers. A prototype system was refined, and iterative changes were made before finalization during a series of operational meetings. The system allows patients to digitally self-report their symptoms and provides longitudinal ePRO symptom data for export into the electronic health record.

Conclusions

Routine ePRO collection has the potential to improve outcomes and hereby also reduce health service costs. We have successfully developed a trial-ready ePRO system for severe psychiatric disorders. The findings were incorporated in the planning of a feasibility pilot trial. Assuming feasibility will be established, the system might be subjected to a certification process evaluation of safety and efficacy including a randomized controlled trial.

"Will it Work as Well on Zoom?" A Natural Experiment During the Covid-19 Pandemic of Delivering Parenting Groups Via Video Conferencing or in Person

While rates of child maltreatment increased during the Covid-19-pandemic, face-to-face interventions to support families got difficult to carry out due to restrictions. Meanwhile, many services do not have access to parenting programs designed for digital or remote delivery. A solution employed by some services was to use video conferencing (VC) to deliver their regular parenting programs. This study examined the effectiveness of the universal group-based parenting program ABC offered through VC instead of on-site meetings during the pandemic. Pre and post measurements were collected from 469 parents participating in either 1) ABC with VC meetings only, 2) on-site meetings only, or 3) blended - a combination of VC and on-site sessions. In addition, 74 group leaders completed a survey about their experiences of VC groups. Analyses showed general improvements in parent practices and child conduct over time, but no differences in effectiveness depending on the format of the parent group (VC, blended, or on-site). Qualitative analyses of group leaders' experiences revealed four key-themes pertaining to both challenges (e.g., concerns about parents' ability to benefit and learn parenting skills) and benefits (e.g., reaching parents who would not have been able to attend physical meetings) of VC groups. Overall, this study showed no significant differences in outcomes between the VC, blended, or on-site format of delivery. There are however limitations of this trial, and results should be considered preliminary. Effectiveness and potential negative consequences of replacing interventions intended to be delivered on-site with VC alternatives need to be further investigated in future trials.

Passive Mobile Self-tracking of Mental Health by Veterans With Serious Mental Illness: Protocol for a User-Centered Design and Prospective Cohort Study

BACKGROUND

Serious mental illnesses (SMI) are common, disabling, and challenging to treat, requiring years of monitoring and treatment adjustments. Stress or reduced medication adherence can lead to rapid worsening of symptoms and behaviors. Illness exacerbations and relapses generally occur with little or no clinician awareness in real time, leaving limited opportunity to modify treatments. Previous research suggests that passive mobile sensing may be beneficial for individuals with SMI by helping them monitor mental health status and behaviors, and quickly detect worsening mental health for prompt assessment and intervention. However, there is too little research on its feasibility and acceptability and the extent to which passive data can predict changes in behaviors or symptoms.

OBJECTIVE

The aim of this research is to study the feasibility, acceptability, and safety of passive mobile sensing for tracking behaviors and symptoms of patients in treatment for SMI, as well as developing analytics that use passive data to predict changes in behaviors and symptoms.

METHODS

A mobile app monitors and transmits passive mobile sensor and phone utilization data, which is used to track activity, sociability, and sleep in patients with SMI. The study consists of a user-centered design phase and a mobile sensing phase. In the design phase, focus groups, interviews, and usability testing inform further app development. In the mobile sensing phase, passive mobile sensing occurs with participants engaging in weekly assessments for 9 months. Three- and nine-month interviews study the perceptions of passive mobile sensing and ease of app use. Clinician interviews before and after the mobile sensing phase study the usefulness and feasibility of app utilization in clinical care. Predictive analytic models are built, trained, and selected, and make use of machine learning methods. Models use sensor and phone utilization data to predict behavioral changes and symptoms.

RESULTS

The study started in October 2020. It has received institutional review board approval. The user-centered design phase, consisting of focus groups, usability testing, and preintervention clinician interviews, was completed in June 2021. Recruitment and enrollment for the mobile sensing phase began in October 2021.

CONCLUSIONS

Findings may inform the development of passive sensing apps and self-tracking in patients with SMI, and integration into care to improve assessment, treatment, and patient outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05023252; https://clinicaltrials.gov/ct2/show/NCT05023252.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39010.

Dialectical Behavior Therapy Skills Training With Music Therapy Interventions for Adults With Serious Mental Illness: A Quasi-Experimental Nonequivalent Control-Group Pilot Study

Dialectical behavior therapy (DBT) improves emotion regulation by building skills in mindfulness, distress tolerance, emotion regulation, and interpersonal effectiveness. The purpose of this pilot study was to compare a DBT skills group with a combined DBT skills and music therapy (MT) group on participant outcomes of attendance, participation, skill practice, and skill knowledge, as well as determine feasibility of study procedures. We used a quasi-experimental nonequivalent control-group design with all groups co-led by a psychologist and a music therapist. Clinicians facilitated twice weekly 45-min groups in 12-week cycles for a total of eight groups over 2 years. The groups alternated DBT-only and DBT+MT; participant data were analyzed for their first cycle attended. The DBT-only group followed a standard DBT skills training format, whereas the DBT+MT group included music therapy interventions as group exercises. Participants (N = 26) were adults with serious mental illness referred to the inpatient psychosocial rehabilitation group (PSR) at a state psychiatric hospital. Participants completed a demographic form, diary cards, and exit interview; clinicians recorded attendance and session participation. Participants in the DBT+MT condition had significantly higher participation levels, slightly higher average attendance, submitted more diary cards, and included more feeling statements than the DBT-only condition. Although interpretations should be approached with caution, the pilot study intervention shows promise. Overall, this study could be implemented as intended under close monitoring, with minor modifications to assist with recruitment and data collection. Modifications, clinical implications, and recommendations for future research are discussed.

NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data

PURPOSE

NeuroBlu is a real-world data (RWD) repository that contains deidentified electronic health record (EHR) data from US mental healthcare providers operating the MindLinc EHR system. NeuroBlu enables users to perform statistical analysis through a secure web-based interface. Structured data are available for sociodemographic characteristics, mental health service contacts, hospital admissions, International Classification of Diseases ICD-9/ICD-10 diagnosis, prescribed medications, family history of mental disorders, Clinical Global Impression-Severity and Improvement (CGI-S/CGI-I) and Global Assessment of Functioning (GAF). To further enhance the data set, natural language processing (NLP) tools have been applied to obtain mental state examination (MSE) and social/environmental data. This paper describes the development and implementation of NeuroBlu, the procedures to safeguard data integrity and security and how the data set supports the generation of real-world evidence (RWE) in mental health.

PARTICIPANTS

As of 31 July 2021, 562 940 individuals (48.9% men) were present in the data set with a mean age of 33.4 years (SD: 18.4 years). The most frequently recorded diagnoses were substance use disorders (1 52 790 patients), major depressive disorder (1 29 120 patients) and anxiety disorders (1 03 923 patients). The median duration of follow-up was 7 months (IQR: 1.3 to 24.4 months).

FINDINGS TO DATE

The data set has supported epidemiological studies demonstrating increased risk of psychiatric hospitalisation and reduced antidepressant treatment effectiveness among people with comorbid substance use disorders. It has also been used to develop data visualisation tools to support clinical decision-making, evaluate comparative effectiveness of medications, derive models to predict treatment response and develop NLP applications to obtain clinical information from unstructured EHR data.

FUTURE PLANS

The NeuroBlu data set will be further analysed to better understand factors related to poor clinical outcome, treatment responsiveness and the development of predictive analytic tools that may be incorporated into the source EHR system to support real-time clinical decision-making in the delivery of mental healthcare services.

Assessing the Use of Data Systems to Estimate Return-on-Investment of Behavioral Healthcare Interventions: Opportunities and Barriers

To improve access to and quality of affordable behavioral healthcare, there is a need for more research to identify which interventions can generate long-term, societal return-on-investment (ROI). Barriers to ROI studies in the behavioral health sector were explored by conducting semi-structured interviews with individuals from key stakeholder groups at state and national behavioral health-related organizations. Limited operating budgets, state-based payer systems, the lack of financial support, privacy laws, and other unique experiences of behavioral health providers and patients were identified as important factors that affect the collection and utilization of data. To comprehensively assess ROI of interventions, it is necessary to improve standardization and data infrastructure across multiple health and non-health systems and clarify or address legal, regulatory, and commercial conflicts.

Practical Approaches to Antipsychotic-Associated Corrected QT Interval Prolongation in Patients With Serious Mental Illness: A Review of Cases

BACKGROUND

There is no consensus for assessment and management of patients with serious mental illness (SMI) who are at risk for cardiac morbidity and mortality due to antipsychotic-associated QTc prolongation.

OBJECTIVE

The objective of this review was to assess methods for risk scoring, QT correction calculation, and clinical management in SMI patients with antipsychotic-associated QTc prolongation.

METHODS

A search was performed in PubMed for case reports that described QTc prolongation in adult patients with schizophrenia or bipolar disorder prescribed an antipsychotic. Reports published in North America between 2000 and 2020 were eligible. The Mayo, Tisdale, and RISQ-PATH scoring tools were applied to cases to categorize risk level.

RESULTS

Seventeen cases were included. Most patients were prescribed a second-generation antipsychotic for schizophrenia, with baseline and maximum QTc values of 429 milliseconds and 545 milliseconds, respectively. The Mayo scoring tool identified 17 (100%) cases as "high risk," Tisdale identified 9 (53%) cases as "moderate risk" and 7 (41%) cases as "low risk," while RISQ-PATH identified 9 (53%) cases as "not low risk" and 8 (47%) cases as "low risk." Three cases reported the QT correction formula utilized (18%). The most common intervention to address antipsychotic-associated QTc prolongation was switching to a different antipsychotic (35%). Approximately one third of patients experienced Torsades de Pointes.

CONCLUSION

There is a lack of standardization for antipsychotic-associated QTc prolongation risk assessment and management in patients with SMI. This review provides real-world data representing actual clinical practice.

Trial-Based Economic Evaluations of Supported Employment for Adults with Severe Mental Illness: A Systematic Review

To identify, appraise, and summarize outcomes reported in trial-based economic evaluations of Individual Placement and Support programs for adults with severe mental illness. Six databases were searched, including Medline, PsycINFO, CINAHL, Cochrane, Scopus, and EconLit. Inclusion criteria were trial-based, full economic evaluations comparing Individual Placement and Support programs to traditional vocational rehabilitation programs for adults 18 years and older with severe mental illness. Study quality was appraised using the Consolidated Health Economic Evaluation Reporting Standards statement. Of the 476 articles identified in the database search, seven were included in the review. Studies conducted across Europe (n = 4) and Japan (n = 1) suggested that Individual Placement and Support may be a cost-effective alternative to traditional vocational rehabilitation programs. Two studies conducted in the United States demonstrated that Individual Placement and Support led to better vocational outcomes, but at neutral or higher costs than traditional vocational rehabilitation, depending on the benefit measure used. Trial-based economic evaluations of supported employment for adults with severe mental illness are limited and heterogeneous. The interpretation of economic outcomes warrants consideration of factors that may impact cost-effectiveness, such as geographical location. Future studies should evaluate whether the benefits of IPS outweigh additional costs for patients and other stakeholders.

Mental Health in Lifestyle Medicine: A Call to Action

Mental health symptoms are pervasive, with 1 in 5 American adults experiencing a mental disorder. Poor mental health is associated with a significant global cost burden, from disability to economic impacts. The field of lifestyle medicine, which emphasizes the role of lifestyle factors in the onset and treatment of disease and well-being, is well suited to address mental health. More recently, there has been attention to the need to incorporate mental health into the field of lifestyle medicine and to attend to the bidirectional role of mental health and lifestyle. Thus, there is a critical opportunity for the field of lifestyle medicine to incorporate mental health into each of the foundational pillars (diet, exercise, substance use, psychological well-being/stress, relationships, sleep) while also specifically targeting lifestyle interventions for populations with mental disorders. The current article provides a framework for the role of mental health within lifestyle medicine by addressing the scope of the problem, clarification regarding mental health, and areas of practice (ie, psychiatry), and providing an overview of the relevant mental health literature for each pillar. This article serves as a call to action to explicitly address and include mental health within all aspects of lifestyle medicine research and practice.

Appraisal of patient-level health economic models of severe mental illness: systematic review

BACKGROUND

Healthcare decision makers require accurate long-term economic models to evaluate the cost-effectiveness of new mental health interventions.

AIMS

To assess the suitability of current patient-level economic models to estimate long-term economic outcomes in severe mental illness.

METHOD

We undertook pre-specified systematic searches in MEDLINE, Embase and PsycINFO to identify reviews and stand-alone publications of economic models of interventions for schizophrenia, bipolar disorder and major depressive disorder (PROSPERO: CRD42020158243). We screened paper titles and abstracts to identify unique patient-level economic models. We conducted a structured extraction of identified models, recording the presence of key predefined model features. Model quality and validation were appraised using the 2014 ISPOR and 2016 AdViSHE model checklists.

RESULTS

We identified 15 unique patient-level models for psychosis and major depressive disorder from 1481 non-duplicate records. Models addressed schizophrenia (n = 6), bipolar disorder (n = 2) and major depressive disorder (n = 7). The predominant model type was discrete event simulation (n = 9). Model complexity and incorporation of patient heterogeneity varied considerably, and only five models extrapolated costs and outcomes over a lifetime horizon. Key model parameters were often based on low-quality evidence, and checklist quality assessment revealed weak model verification procedures.

CONCLUSIONS

Existing patient-level economic models of interventions for severe mental illness have considerable limitations. New modelling efforts must be supplemented by the generation of good-quality, contemporary evidence suitable for model building. Combined effort across the research community is required to build and validate economic extrapolation models suitable for accurately assessing the long-term value of new interventions from short-term clinical trial data.

Relationship Between Volunteering and Perceived General Health of Individuals with Serious Mental Illness

Volunteering has been found to be a significant predictor of improved health among the general population. Yet, little is known about the relationship between volunteering and perceived general health among individuals with serious mental illness (SMI). Using data obtained from the 2014 California Health Interview Survey (N = 1127), this study examined the extent to which volunteering is associated with perceived general health of individuals with SMI. Study findings indicate that individuals who engage in volunteering are more likely to report better health status when compared to those who do not engage in volunteering.

The technology specialist: a 21st century support role in clinical care

Mental health clinicians, clients, and researchers have shown keen interest in using technology to support mental health recovery. However, technology has not been routinely integrated into clinical care. Clients use a wide range of digital tools and apps to help manage their mental health, but clinicians rarely discuss this form of self-management in clinical interactions. This absence of communication is concerning because the safety and quality of the digital tools and apps people use may negatively affect their mental health outcomes. Mental health systems could benefit from someone to help identify technology-based supports that reflect current evidence and minimize privacy and security concerns. This technology specialist may also enhance the therapeutic bond between the client and the clinician. In working with a technology specialist, clients may begin to gain a sense of control over their mental health, and perhaps use fewer mental health services.