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Mobile sensing-based depression severity assessment could complement the subjective questionnaires-based assessment currently used in practice. However, previous studies on mobile sensing for depression severity assessment were conducted on homogeneous mental health condition participants; evaluation of possible generalization across heterogeneous groups has been limited. Similarly, previous studies have not investigated the potential of free-living audio data for depression severity assessment. Audio recordings from free-living could provide rich sociability features to characterize depressive states. We conducted a study with 11 healthy individuals, 13 individuals with major depressive disorder, and eight individuals with schizoaffective disorders. Communication logs and location data from the participants’ smartphones and continuous audio recordings of free-living from a wearable audioband were obtained over a week for each participant. The depression severity prediction model trained using communication log and location data features had a root mean squared error (rmse) of 6.80. Audio-based sociability features further reduced the rmse to 6.07 (normalized rmse of 0.22). Audio-based sociability features also improved the F1 score in the five-class depression category classification model from 0.34 to 0.46. Thus, free-living audio-based sociability features complement the commonly used mobile sensing features to improve depression severity assessment. The prediction results obtained with mobile sensing-based features are better than the rmse of 9.83 (normalized rmse of 0.36) and the F1 score of 0.25 obtained with a baseline model. Additionally, the predicted depression severity had a significant correlation with reported depression severity (correlation coefficient of 0.76, p < 0.001). Thus, our work shows that mobile sensing could model depression severity across participants with heterogeneous mental health conditions, potentially offering a screening tool for depressive symptoms monitoring in the broader population.

In 2020, the National Survey on Drug Use and Health estimated that 40.3 million Americans met the criteria for a substance use disorder (SUD) in the past year. Yet few FDA-approved treatments exist for SUDs—and no explicit treatment guidelines. When it comes to multi-SUDs in particular, the dearth of literature is notable. This is where Pharmacotherapy for Complex Substance Use Disorders: A Practical Guide comes in. Fifteen addiction psychiatrists have contributed to this volume, bringing their clinical experience to bear for readers that include mental health and primary care clinicians. Introductory chapters provide a necessary framework, offering an overview of SUDs; general guidelines for taking a history, making a medical and a psychiatric evaluation, and forming a diagnosis; and a discussion of the neurobiology of addiction. In the subsequent chapters, the volume delves into maintenance pharmacological treatment for co-occurring substances that include • Alcohol• Opioids• Psychostimulants• Novel psychoactive substances Uniquely, this guide also discusses psychopharmacological approaches to working with special patient populations—adolescents, LGBTQ+ individuals, and pregnant people among them. Filled with tables for ease of reference both when diagnosing and treating patients, and bolstered by evidence-based, actionable information, Pharmacotherapy for Complex Substance Use Disorders: A Practical Guide sets itself apart as an indispensable resource for all providers aiding individuals on their journeys of recovery.

The media and public health generally focus on the biological and physical ramifications of epidemics. Mental health issues that coincide with emerging diseases and epidemics are rarely examined and sometimes, even eschewed due to cultural considerations. Psychiatric manifestations of various infectious diseases, especially with a focus on Ebola Virus disease (EVD) and Zika Virus, are discussed in this commentary to illustrate the continued need of care after the resolution of the actual illness. Various infectious diseases have associations with mental illness, such as an increased risk of obsessive-compulsive disorders and Tourette syndrome in children with Group B streptococcal infection. Current EVD literature does not demonstrate a strong association of mental illness symptoms or diseases but there is a necessity of care that extends beyond the illness. Patients and their families experience depression, anxiety, trauma, suicidal ideation, panic and other manifestations. Zika virus has been associated neuronal injury, genetic alteration that affects fetal development and detrimental maternal mental health symptoms are being documented. While funding calls from the international community are present, there are no specific epidemiological data or fiscal estimates solely for mental health during or after infectious diseases epidemics or disasters that support health care providers and strengthen policies and procedures for responding to such situations. Therefore, those on the frontlines of epidemics including emergency physicians, primary care providers and infectious disease specialists should serve communicate this need and advocate for sustained and increased funding for mental health programs to heighten public awareness regarding acute psychiatric events during infectious diseases outbreaks and offer treatment and support when necessary.

In 2024, >6 million US ED visits for primary psychiatric complaints required medical clearance before psychiatric evaluation. However, clearance methods vary across institutions. Tools such as the SMART checklist, Shah's Score, and Triage Algorithm for Psychiatric Screening (TAPS) score aim to standardize this process. Our purpose was to compare the utility of these tools for the medical clearance of patients with psychiatric ED. We retrospectively reviewed adult ED patients' Electronic Medical Records (EMRs) with psychiatric chief complaints at a large US urban teaching hospital, excluding pregnancy, incarceration, or incomplete records. We applied the three scores retrospectively to assess the accuracy. Outcomes included disposition to the psychiatric unit or discharge vs. medical admission. The patients were followed up for 30 days to track revisits. The accuracy of Shah's, TAPS, and SMART checklists were calculated and analyzed using Pearson's χ2 test. Of 1613 screened patients, 507 met the inclusion criteria. Their mean (SD) age was 39.1 (±14) years; most were male (66.7 %) and African American (49.7 %). Suicidality was the most common complaint (49.9 %); 55.0 % presented voluntarily, and 89.9 % underwent laboratory tests. Dispositions included ED discharge (61.9 %), psychiatric (35.5 %), or medical admission (2.6 %). The SMART checklist had the highest sensitivity (83.3 %, 95 % CI = 51.6 %–97.9 %). The TAPS and Shah's score sensitivities were 66.6 % (34.9–90.1 %) and 33.3 % (09.9 %–65.1 %), respectively. The specificities of Shah's score, TAPS score, and SMART were 76.9 %(73 %–80.6 %), 36.6 %(32.1–40.8 %), and 44.9 %(40.4 %–49.4 %), respectively. NPVs were 99.1 % (96.8 %–99.9 %), 97.8 % (94.5 %–99.4 %), and 97.9 % (96.0 %–99.1 %) for SMART, TAPS, and Shah's, respectively. The SMART Checklist missed two patients: one with thyroid cancer and one admitted for inability to perform activities of daily living (ADLs). The SMART checklist showed higher sensitivity and NPV than the other tools for identifying psychiatric patients who did not require medical evaluation. However, further prospective validation is required to confirm these findings.

Introduction. Suicide is one of the leading causes of death across different age groups. The persistence of suicidal ideation and the progression of suicidal ideations to action could be related to impulsivity, the tendency to act on urges with low temporal latency, and little forethought. Quantifying impulsivity could thus help suicidality estimation and risk assessments in ideation-to-action suicidality frameworks. Methods. To model suicidality with impulsivity quantification, we obtained questionnaires, behavioral tests, heart rate variability (HRV), and resting state functional magnetic resonance imaging measurements from 34 participants with mood disorders. The participants were categorized into three suicidality groups based on their Mini-International Neuropsychiatric Interview: none, low, and moderate to severe. Results. Questionnaire and HRV-based impulsivity measures were significantly different between the suicidality groups with higher subscales of impulsivity associated with higher suicidality. A multimodal system to characterize impulsivity objectively resulted in a classification accuracy of 96.77% in the three-class suicidality group prediction task. Conclusions. This study elucidates the relative sensitivity of various impulsivity measures in differentiating participants with suicidality and demonstrates suicidality prediction with high accuracy using a multimodal objective impulsivity characterization in participants with mood disorders.

Impulsivity represents an individual’s tendency to act on urges without sufficient forethought. Heightened impulsivity is a hallmark of many mental health disorders. Objective impulsivity assessments could improve risk evaluation, diagnosis, and behavioral outcome monitoring in impulsivity-related health disorders. Towards objective impulsivity assessment, in this work, we identify impulsivity correlates in objective measurements, investigate their complementarity, and contrast impulsivity mechanisms across health conditions. We analyzed behavioral tests, heart rate variability (HRV), and fMRI-based brain connectivity in 227 healthy participants and 34 participants with mood disorders. Impulsivity dimensions had complementary correlates in objective measurements, with fMRI providing the strongest correlates. Multimodal assessment provided high r-squared (adjusted) values in modeling impulsivity of the mood disorder participants (e.g., r-squared of 0.73, p  < 0.001 for attentional impulsivity) but low r-squared for healthy participants (the best r-squared being 0.17, p  < 0.001 for sensation seeking impulsivity). The differing association between impulsivity dimensions across the two populations likely indicates a health condition-specific impulsivity mechanism across populations. The complementary nature of objective impulsivity correlates across populations demonstrates the distributed signature of multidimensional impulsivity, likely capturing the complexity of behavioral modeling. Lay Summary Impulsivity is commonly implicated in many mental health disorders. We examined behavioral tests, heart rate variability, and brain connectivity (via fMRI) as objective methods to assess impulsivity in 227 healthy individuals and 34 individuals with mood disorders. fMRI provided the strongest correlates of impulsivity, with multimodal assessment providing the most accurate models of impulsivity across health conditions. Our work lays the ground for future studies to develop robust impulsivity assessments across different populations.

Introduction Ethical concerns have been raised by both current and historically controversial neurosurgical interventions for treatment-refractory schizophrenia and schizoaffective disorder (TR-SZ). Considering advances in next-generation deep brain stimulation (DBS), initial success in treating a few cases of TR-SZ, and how challenging trial enrollment is, transparency and disseminating knowledge about DBS is important, as is input from involved groups. Here information was presented about DBS as an experimental treatment option for TR-SZ to stakeholders to gauge enthusiasm after consideration of potential risks and benefits. Methods Stakeholders were presented with information about DBS (total n  = 629). Opinions about whether DBS should be an option for people with TR-SZ and acceptable response rates considering DBS risks were collected from research participants with SZ, treatment-refractory Parkinson’s disease (TR-PD) approved for DBS, caregivers for either SZ or TR-PD participants, and attendees at medical school presentations. In addition, the attendees were asked to decide whether DBS is appropriate for 4 cases who want DBS, one with PD, 2 with OCD and 1 with SZ. Chi-square, pairwise comparisons, and Duncan Multiple Range Test were performed with significance at p  < 0.05. Results Most (83%) research participants and presentation audience members agreed that DBS should be an option for TR-SZ and 40% thought the potential benefits outweigh the risks of DBS with at least a 41–60% response rate. Audience approval of DBS was similar for the PD (30%), SZ (52%) and the OCD case with psychosis (56%), but there was a higher rate of approval (77%) for the OCD case whose compulsions involved self-harm. The majority (73–86%) of the audience thought that they would want to try DBS if they had TR-PD, TR-OCD, or TR-SZ. Conclusions Despite difficulty in recruiting patients for DBS clinical trials for TR-SZ, the consensus among 83% of stakeholders was that DBS should be an option for people with severe TR-SZ. Our approach to disseminate general knowledge then gather opinions among diverse stakeholders was to ensure the development of DBS clinical trials for the new indication TR-SZ is a relevant option despite the known difficulties in enrollment. These findings may help prevent disparities in access to advanced DBS therapeutics.

In this mini-review, we discuss the fundamentals of using technology in mental health diagnosis and tracking. We highlight those principles using two clinical concepts: (1) cravings and relapse in the context of addictive disorders and (2) anhedonia in the context of depression. This manuscript is useful for both clinicians wanting to understand the scope of technology use in psychiatry and for computer scientists and engineers wishing to assess psychiatric frameworks useful for diagnosis and treatment. The increase in smartphone ownership and internet connectivity, as well as the accelerated development of wearable devices, have made the observation and analysis of human behavior patterns possible. This has, in turn, paved the way to understand mental health conditions better. These technologies have immense potential in facilitating the diagnosis and tracking of mental health conditions; they also allow the implementation of existing behavioral treatments in new contexts (e.g., remotely, online, and in rural/underserved areas), and the possibility to develop new treatments based on new understanding of behavior patterns. The path to understand how to best use technology in mental health includes the need to match interdisciplinary frameworks from engineering/computer sciences and psychiatry. Thus, we start our review by introducing bio-behavioral sensing, the types of information available, and what behavioral patterns they may reflect and be related to in psychiatric diagnostic frameworks. This information is linked to the use of functional imaging, highlighting how imaging modalities can be considered “ground truth” for mental health/psychiatric dimensions, given the heterogeneity of clinical presentations, and the difficulty of determining what symptom corresponds to what disease. We then discuss how mental health/psychiatric dimensions overlap, yet differ from, psychiatric diagnoses. Using two clinical examples, we highlight the potential agreement areas in assessment/management of anhedonia and cravings. These two dimensions were chosen because of their link to two very prevalent diseases worldwide: depression and addiction. Anhedonia is a core symptom of depression, which is one of the leading causes of disability worldwide. Cravings, the urge to use a substance or perform an action (e.g., shopping, internet), is the leading step before relapse. Lastly, through the manuscript, we discuss potential mental health dimensions.

In November 2023, a variety of disparate health organizations formed an international coalition to consolidate efforts and develop collaborative strategies in response to the increasing critical healthcare challenges caused by the recent war in Gaza. The coalition includes medical and public health experts, humanitarian practitioners, academics, and health policy-makers from across the world. Their membership has not much to do with mainstream humanitarian organisations. It is lead by the diaspora from the region. Their vision is the long-term reconstruction of the health system in Gaza while responding the most urgent needs. This collective effort will require explicit efforts to speak with one voice and avoid duplication. This collective movement may be an orginal initiative that may be able to beat the expected international donor fatigue.