Rebuilding the health sector in Gaza: alternative humanitarian voices.

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.

Predicting aggressive behavior in psychiatric patients in emergency department: A systematic literature review.

INTRODUCTION: Aggression and violence are major concerns in emergency departments (EDs), and have negative consequences for patient and staff health and safety. Few validated tools exist for identifying patients at risk of agitation. This study conducted a systematic literature review to identify and summarize the scores that predict aggressive behavior in EDs. METHODS: The search included articles published between Jan 1st, 1987, and Dec 31st, 2022, using the terms "aggress*," "violent*," "emergency," "acute," "score," or "scale." RESULTS: Ten scores were found to be relevant, with eight of the developed scores intended for use in EDs. The Aggressive Behavior Risk Assessment Tool (ABRAT) was found to be sensitive (84.3%) and specific (95.3%). The Brøset Violence Checklist (BVC) was highly specific (99.4%), whereas the Violence Screening Checklist (VSC) was less sensitive (57.2%) and specific (45.7%). The violence and aggression (OVA)/BVC checklist was found to significantly decrease the number of security call activations (P < 0.001). The Behavioral Activity Rating Scale (BARS) and OVA/BVC scores were the shortest, with seven and six items, respectively. CONCLUSION: The OVA/BVC checklist is a valuable tool for predicting and preventing violence in the EDs. Future prospective studies should investigate its effectiveness.

Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder.

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.

Postsurgical morbidity and mortality favorably informs deep brain stimulation for new indications including schizophrenia and schizoaffective disorder.

Background: Deep brain stimulation (DBS) shows promise for new indications like treatment-refractory schizophrenia in early clinical trials. In the first DBS clinical trial for treatment refractory schizophrenia, despite promising results in treating psychosis, one of the eight subjects experienced both a symptomatic hemorrhage and an infection requiring device removal. Now, ethical concerns about higher surgical risk in schizophrenia/schizoaffective disorder (SZ/SAD) are impacting clinical trial progress. However, insufficient cases preclude conclusions regarding DBS risk in SZ/SAD. Therefore, we directly compare adverse surgical outcomes for all surgical procedures between SZ/SAD and Parkinson's disease (PD) cases to infer relative surgical risk relevant to gauging DBS risks in subjects with SZ/SAD. Design: In the primary analysis, we used browser-based statistical analysis software, TriNetX Live (trinetx.com TriNetX LLC, Cambridge, MA), for Measures of Association using the Z-test. Postsurgical morbidity and mortality after matching for ethnicity, over 39 risk factors, and 19 CPT 1003143 coded surgical procedures from over 35,000 electronic medical records, over 19 years, from 48 United States health care organizations (HCOs) through the TriNetX Research Network™. TriNetXis a global, federated, web-based health research network providing access and statistical analysis of aggregate counts of deidentified EMR data. Diagnoses were based on ICD-10 codes. In the final analysis, logistic regression was used to determine relative frequencies of outcomes among 21 diagnostic groups/cohorts being treated with or considered for DBS and 3 control cohorts. Results: Postsurgical mortality was 1.01-4.11% lower in SZ/SAD compared to the matched PD cohort at 1 month and 1 year after any surgery, while morbidity was 1.91-2.73% higher and associated with postsurgical noncompliance with medical treatment. Hemorrhages and infections were not increased. Across the 21 cohorts compared, PD and SZ/SAD were among eight cohorts with fewer surgeries, nine cohorts with higher postsurgical morbidity, and fifteen cohorts within the control-group range for 1-month postsurgical mortality. Conclusions: Given that the subjects with SZ or SAD, along with most other diagnostic groups examined, had lower postsurgical mortality than PD subjects, it is reasonable to apply existing ethical and clinical guidelines to identify appropriate surgical candidates for inclusion of these patient populations in DBS clinical trials.

Technology Implementation for Mental Health End Users: A Model to Guide Digital Transformation for Inpatient Mental Health Professionals.

Digital transformation is the adoption of digital technologies by an entity in an effort to increase operational efficiency. In mental health care, digital transformation entails technology implementation to improve the quality of care and mental health outcomes. Most psychiatric hospitals rely heavily on "high-touch" interventions or those that require in-person, face-to-face interaction with the patient. Those that are exploring digital mental health care interventions, particularly for outpatient care, often copiously commit to the "high-tech" model, losing the crucial human element. The process of digital transformation, especially within acute psychiatric treatment settings, is in its infancy. Existing implementation models outline the development of patient-facing treatment interventions within the primary care system; however, to our knowledge, there is no proposed or established model for implementing a new provider-facing ministration tool within an acute inpatient psychiatric setting. Solving the complex challenges within mental health care demands that new mental health technology is developed in concert with a use protocol by and for the inpatient mental health professional (IMHP; the end user), allowing the "high-touch" to inform the "high-tech" and vice versa. Therefore, in this viewpoint article, we propose the Technology Implementation for Mental-Health End-Users framework, which outlines the process for developing a prototype of an IMHP-facing digital intervention tool in parallel with a protocol for the IMHP end user to deliver the intervention. By balancing the design of the digital mental health care intervention tool with IMHP end user resource development, we can significantly improve mental health outcomes and pioneer digital transformation nationwide.

"I have nothing more to give": Disparities in burnout and the protective role of immigrant status during the COVID-19 pandemic.

Burnout is an epidemic, with deleterious effects on individuals, patient care, and healthcare systems. The Coronavirus Disease 2019 (COVID-19) pandemic may be exacerbating this problem. We aimed to explore socio-cultural and gender norms that modulate burnout development in physicians during the pandemic and analyze any disparities associated with gender, marital and immigration status and work-life balance. We conducted an online cross-sectional survey of physicians (August-November, 2021): The Maslach Burnout Inventory-Human Services Survey (MBI-HSS) was used to measure burnout, combined with a validated survey assessing work-life balance. Demographic data was obtained for each participant. MBI-HSS subscales were measured, along with work and home related changes due to COVID-19. The association between life changes due to COVID-19 and odds of burnout was estimated by logistic regression. Complementary analysis was performed to determine factors most associated with burnout. 352 respondents were analyzed. There was a high prevalence of burnout. Over half of individuals reported a high degree of emotional exhaustion (EE) (56%). 83% of individuals reported at least one life factor changed due to COVID-19. Home-related life changes due to COVID-19 were associated with 143% higher odds of emotional burnout [adjusted odds ratio (aOR) 2.43; 95% confidence interval (CI) 1.49, 3.98] after covariate adjusted analysis. High EE was most evident when there were three or more life changes, suggesting a cumulative effect. First-generation immigrants, older physicians, and trainees were identified as protective factors. Although female gender was identified as a factor related to EE through forward selection, this was not statistically significant (aOR 1.34; 95% CI 0.80, 2.24). Burnout remains pervasive among physicians. We highlight new risk factors for EE (home-life changes due to COVID-19), and protective factors (first-generation immigrants) not previously explored. Understanding burnout and its disparities allows for improved mitigation strategies, decreasing its deleterious effects.

Evolution of Mood Symptomatology Through the COVID-19 Pandemic: Findings From the CovidSense Longitudinal Study.

Background The severe acute respiratory syndrome coronavirus 2 global pandemic, with its associated coronavirus disease 2019 (COVID-19) illness, has led to significant mental, physical, social, and economic hardships. Physical distancing, isolation, and fear of illness have significantly affected the mental health of people worldwide. Several studies have documented the cross-sectional elevated prevalence of mental anguish, but due to the sudden nature of the pandemic, very few longitudinal studies have been reported, especially covering the first phase of the pandemic. CovidSense, a longitudinal adaptive study, was initiated to answer some key questions: how did the pandemic and related social and economic conditions affect depression, which groups showed more vulnerability, and what protective factors emerged as the pandemic unfolded? Methodology CovidSense was deployed from April to December 2020. The adaptive design enabled adaption to fluctuating demographics/health status. Participants were regularly queried via SMS messages about their mental health, physical health, and life circumstances. The study included 1,190 participants who answered a total of 18,783 survey panels. This was a prospective longitudinal cohort study following adult participants in the general population through the COVID-19 pandemic. The participant cohort reported self-assessed measures ranging from subjective mood ratings and substance use to validated questionnaires, such as the Quick Inventory of Depressive Symptoms (QIDS) and Cognitive and Affective Mindfulness Scale-Revised (CAMS-R). Results Participants with pre-existing physical (especially pulmonary) or mental conditions had overall higher levels of depression, as measured by the QIDS and self-reported mood. Participants with pre-existing conditions also showed increased vulnerability to the stress caused by watching the news and the increase in COVID-19 cases. Younger participants (aged 18-25 years) were more affected than older groups. People with severe levels of depression had the most variation in QIDS scores, whereas individuals with none to low depressive scores had the most variability in self-reported mood fluctuations. Conclusions The effects of pandemic-related chronic stress were predominant in young adults and individuals with pre-existing mental and medical conditions regardless of whether they had acquired COVID-19 or not. These results point to the possibility of allocating preventive as well as treatment resources based on vulnerability.

Turning data into better mental health: Past, present, and future.

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.

Privacy-Preserving Social Ambiance Measure From Free-Living Speech Associates With Chronic Depressive and Psychotic Disorders.

A social interaction consists of contributions by the individual, the environment and the interaction between the two. Ideally, to enable effective assessment and interventions for social isolation, an issue inherent to depressive and psychotic illnesses, the isolation must be identified in real-time and at an individual level. However, research addressing sociability deficits is largely focused on determining loneliness, rather than isolation, and lacks focus on the richness of the social environment the individual revolves in. In this paper, We describe the development of an automated, objective and privacy-preserving Social Ambiance Measure (SAM) that converts unconstrained audio recordings collected from wrist-worn audio-bands into four levels, ranging from none to active. The ambiance levels are based on the number of simultaneous speakers, which is a proxy for overall social activity in the environment. Results show that social ambiance patterns and time spent at each ambiance level differed between participants with depressive or psychotic disorders and healthy controls. Individuals with depression/psychosis spent less time in diverse environments and less time in moderate/active ambiance levels. Moreover, social ambiance patterns are found associated with the severity of self-reported depression, anxiety symptoms and personality traits. The results in this paper suggest that objectively measured social ambiance can be used as a marker of sociability, and holds potential to be leveraged to better understand social isolation and develop effective interventions for sociability challenges, thus improving mental health outcomes.

Tracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Study.

BACKGROUND: Depression carries significant financial, medical, and emotional burden on modern society. Various proof-of-concept studies have highlighted how apps can link dynamic mental health status changes to fluctuations in smartphone usage in adult patients with major depressive disorder (MDD). However, the use of such apps to monitor adolescents remains a challenge. OBJECTIVE: This study aimed to investigate whether smartphone apps are useful in evaluating and monitoring depression symptoms in a clinically depressed adolescent population compared with the following gold-standard clinical psychometric instruments: Patient Health Questionnaire (PHQ-9), Hamilton Rating Scale for Depression (HAM-D), and Hamilton Anxiety Rating Scale (HAM-A). METHODS: We recruited 13 families with adolescent patients diagnosed with MDD with or without comorbid anxiety disorder. Over an 8-week period, daily self-reported moods and smartphone sensor data were collected by using the Smartphone- and OnLine usage-based eValuation for Depression (SOLVD) app. The evaluations from teens' parents were also collected. Baseline depression and anxiety symptoms were measured biweekly using PHQ-9, HAM-D, and HAM-A. RESULTS: We observed a significant correlation between the self-evaluated mood averaged over a 2-week period and the biweekly psychometric scores from PHQ-9, HAM-D, and HAM-A (0.45≤|r|≤0.63; P=.009, P=.01, and P=.003, respectively). The daily steps taken, SMS frequency, and average call duration were also highly correlated with clinical scores (0.44≤|r|≤0.72; all P<.05). By combining self-evaluations and smartphone sensor data of the teens, we could predict the PHQ-9 score with an accuracy of 88% (23.77/27). When adding the evaluations from the teens' parents, the prediction accuracy was further increased to 90% (24.35/27). CONCLUSIONS: Smartphone apps such as SOLVD represent a useful way to monitor depressive symptoms in clinically depressed adolescents, and these apps correlate well with current gold-standard psychometric instruments. This is a first study of its kind that was conducted on the adolescent population, and it included inputs from both teens and their parents as observers. The results are preliminary because of the small sample size, and we plan to expand the study to a larger population.

A review and preview of developments in the measurement of sociability.

Sociability is a complex, multifactorial trait. Its importance is underscored by a multitude of negative physical and mental health effects related to loneliness and social isolation. However, current measures of sociability primarily rely on subjective recall and self- report, which have inherent weaknesses and limitations. Although objective and automatic measurements could help to avoid some of these issues, they are still in early stages of development. In this article, the authors review past and present methods of measuring sociability and social interactions. This encompasses both subjective and objective subsets of qualitative and quantitative measurement modalities to gain a broader, more accurate perspective on sociability. Through an analysis of advantages and disadvantages of measurement methods within these categories, a foundational knowledge of sociability measurement can be understood. Utilizing current technology and research methods holds promise to more accurately represent individuals' social networks and social patterns.

Findings From a Trial of the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) Application: What Do Apps Really Tell Us About Patients with Depression? Concordance Between App-Generated Data and Standard Psychiatric Questionnaires for Depression and Anxiety.

OBJECTIVE: Depression imposes a notable societal burden, with limited treatment success despite multiple available psychotherapy and medications choices. Potential reasons may include the heterogeneity of depression diagnoses and the presence of comorbid anxiety symptoms. Despite technological advances and the introduction of many mobile phone applications (apps) claiming to relieve depression, major gaps in knowledge still exist regarding what apps truly measure and how they correlate with psychometric questionnaires. The goal of this study was to evaluate whether mobile daily mood self-ratings may be useful in monitoring and classifying depression symptoms in a clinically depressed population compared with standard psychometric instruments including the Patient Health Questionaire-9 (PHQ-9), the Hamilton Rating Scale for Depression (HAM-D), and the Hamilton Anxiety Rating Scale (HAM-A). METHOD: For this study, 22 patients with major depressive disorder with or without comorbid anxiety disorder were recruited. The diagnosis of depression was confirmed through the Mini International Neuropsychiatric Interview (MINI). Over an 8-week period, daily moods were self-reported through the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) application, a custom-designed application that was downloaded onto patients' mobile devices. Depression and anxiety symptoms were also measured biweekly using the HAM-D, HAM-A, and PHQ-9. RESULTS: Significant correlations were observed among self-evaluated mood, daily steps taken, SMS (text) frequency, average call duration, and biweekly psychometric scores (|r|>0.5, P<0.05). The correlation coefficients were higher in individuals with more severe depressive symptoms. CONCLUSIONS: Although this study, given its limited sample size, was exploratory in nature, it helps fill a significant gap in our knowledge of the concordance between ratings obtained on the Ham-D, Ham-A, and the PHQ-9 psychometric instruments and data obtained via a smartphone app. These questionnaires represent gold-standard, commonly used psychiatric research/clinical instruments, and, thus, this information can serve as a foundation for digital phenotyping for depression and pave the way for interventional studies using smartphone applications.

True Costs of Medical Clearance: Accuracy and Disagreement between Psychiatry and Emergency Medicine Providers.

INTRODUCTION: Medical clearance is required to label patients with mental illness as free of acute medical concerns. However, tests may extend emergency department lengths of stay and increase costs to patients and hospitals. The objective of this study was to determine how knowledgeable emergency and psychiatric providers are about the costs of tests used for medical clearance. MATERIALS AND METHODS: We surveyed the department of psychiatry (Psych) and department of emergency medicine (EM) faculty and residents to obtain their estimates of the costs of 18 laboratory/imaging studies commonly used for medical clearance. Survey responses were analyzed using the Wilcoxon signed-rank test to compare the median cost estimates between residents and faculty in EM and Psych. RESULTS: A total of 99 physicians (response rate, 47.8%) completed the survey, including 47 faculty (EM = 28; Psych = 20) and 52 residents (EM = 29; Psych = 23). Across all the groups, cost estimates for tests were inaccurate, off by several hundred dollars for three tests, and by $13-$80 for 15. Significant differences between EM and Psych providers for estimated median costs of specific tests included between residents for urine drug screens (EM: $800; Psych: $50; P < 0.0001) and ECG (EM: $25; Psych: $75; P = 0.004); between faculty for urinalysis (EM: $40; Psych: $18; P = 0.020) and urine drug screen (EM: $100; Psych: $10; P < 0.0001); and between all physicians for urine drug screen (EM: $500; Psych: $50; P < 0.0001). CONCLUSION: Further education on the financial costs of medical clearance is needed to inform workup decisions and consensus between emergency and psychiatric providers.

Like the Eye of the Tiger: Inpatient Psychiatric Facility Exclusionary Criteria and Its "Knockout" of the Emergency Psychiatric Patient.

CONTEXT: Over 6% of all emergency department (ED) visits in the United States involve primary mental health or behavioral issues. The patients are stabilized in the ED but frequently require admission to an inpatient psychiatric unit or institution for longer term treatment and management. To facilitate this process, an emergency physician (EP) must first "medically clear" the patient as stable for transfer. At present, there is no interdisciplinary consensus regarding the necessary elements of the medical clearance or stability assessment process. In addition to satisfy the vague requirement for medical clearance, the EP must abide by the rules of the inpatient facilities before his/her patient is accepted. SETTINGS AND DESIGN: This manuscript summarizes the admission exclusionary criteria of inpatient psychiatric units in the Houston-Galveston metro area. SUBJECTS AND METHODS: we pooled the exclusionary criteria of all the facilities patients with mental illness can be sent to in the Houston-Galveston metropolitan area, and divided those criteria by categories. RESULTS: Pooled exclusionary criteria congregate into 1. preexisting or current medical condition and capabilities (e.g. hypertensive urgency, pregnancy, acute alcohol intoxication), 2. exclusionary criteria related to administrative burdens that may impact staffing or require advanced equipment/training e.g. autism spectrum disorders, intellectual disabilities, respiratory isolation or daily hemodialysis, 3. laboratory and ancillary testing required by inpatient facilities before acceptance of the patient. CONCLUSIONS: Of the inpatient units in the Houston-Galveston area, facilities lack a unified staffing model, ancillary services, but the various challenges (e.g., limited staffing and ancillary services) and different skills offered (e.g., geriatric care) are reflected in exclusionary criteria in a partially overlapping, but not fully uniform, way. The variation in number and kinds of exclusionary criteria further complicate the admission process and often serve as a bottleneck in the securing an inpatient bed.

Difficult Patients in the Emergency Department: Personality Disorders and Beyond.

Physician-patient encounters in clinical settings, especially in the emergency department, can be of varying degrees of difficulty. Medically complicated, challenging cases can be paradoxically rewarding, whereas psychologically driven difficulty is frustrating and counterproductive for patient care. This article presents 3 different complementary perspectives on difficult patients: clinical presentations, manifestations of personality traits and disorders in clinical settings, and how physician feelings may affect care. Management strategies are discussed.

Emergency Department Medical Clearance of Patients with Psychiatric or Behavioral Emergencies, Part 1.

Patients presenting to the emergency department with mental illness or behavioral complaints merit workup for underlying physical conditions that can trigger, mimic, or worsen psychiatric symptoms. However, interdisciplinary consensus on medical clearance is lacking, leading to wide variations in quality of care and, quite often, poor medical care. Psychiatry and emergency medicine specialty guidelines support a tailored, customized approach. This article summarizes best-practice approaches to the medical clearance of patients with psychiatric illness, tips on history taking, system reviews, clinical or physical examination, and common pitfalls in the medical clearance process.

Emergency Department Medical Clearance of Patients with Psychiatric or Behavioral Emergencies, Part 2: Special Psychiatric Populations and Considerations.

Patients who present to the emergency department (ED) with mental illness or behavioral complaints merit workup for underlying physical conditions that can trigger, mimic, or worsen psychiatric symptoms. However, there are wide variations in quality of care for these individuals. Psychiatry and emergency medicine specialty guidelines support a tailored, customized approach to patients. Our group has long advocated a dynamic comanagement approach for medical clearance in the ED, and this article summarizes best-practice approaches to the medical clearance of patients with psychiatric illness, tips on history taking, system reviews, clinical/physical examination, and common pitfalls in the medical clearance process.

Addictive Disorders in Adolescents.

Addictive disorders in youth represent a dynamic field characterized by shifting patterns of substance use and high rates of experimentation, while retaining the risky behaviors and negative outcomes associated with established drug classes. Youth/adolescents are also at the forefront of use of new technologies, and non-substance-related disorders are pertinent. These disorders present with similar pictures of impairment, and can be diagnosed following the same principles. An underlying mental disorder and the possibility of a dual diagnosis need to be assessed carefully, and optimal treatment includes psychosocial treatments with applicable pharmacologic management, the latter representing an expanding field.