Many studies have explored the relationship between the demographics, diagnosis and treatment variables on length of stay in an acute psychiatric hospital. These studies have been able to account for about 10-37% of the variance in the length of stay. The relevant findings impacting the length of stay are shown in Table 2 .

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In a 2012 survey, in the United States alone, there were more than 35 000 reported suicides with approximately 1800 of being psychiatric inpatients. Recent Centers for Disease Control and Prevention (CDC) reports indicate an upward trend in these numbers. In psychiatric facilities, staff perform intermittent or continuous observation of patients manually in order to prevent such tragedies, but studies show that they are insufficient, and also consume staff time and resources. In this paper, we present the Watch-Dog system, to address the problem of detecting self-harming activities when attempted by in-patients in clinical settings. Watch-Dog comprises of three key components-Data sensed by tiny accelerometer sensors worn on wrists of subjects; an efficient algorithm to classify whether a user is active versus dormant (i.e., performing a physical activity versus not performing any activity); and a novel decision selection algorithm based on random forests and continuity indices for fine grained activity classification. With data acquired from 11 subjects performing a series of activities (both self-harming and otherwise), Watch-Dog achieves a classification accuracy of , , and for same-user 10-fold cross-validation, cross-user 10-fold cross-validation, and cross-user leave-one-out evaluation, respectively. We believe that the problem addressed in this paper is practical, important, and timely. We also believe that our proposed system is practically deployable, and related discussions are provided in this paper.

Schizophrenia is a severe mental illness with a lifetime prevalence of approximately one percent worldwide. Maintenance antipsychotic treatment has been effective in preventing relapses in long-term follow-up studies. Logically it can be proposed that long-acting injectable antipsychotics (LAI) might reduce both unintentional and intentional nonadherence. Long-acting injectable aripiprazole was approved for the treatment of schizophrenia by the U.S. FDA on 28th February 2013 and will be marketed under the name Abilify Maintena. Aripiprazole LAI (ALAI) is a lyophilized powder that needs to be reconstituted with sterile water to form an injectable suspension without affecting the original molecule. The monthly injection interval is very attractive since patients prefer fewer injections. From a tolerability perspective, ALAI appears to be both weight neutral and lacking metabolic side effects. This can confer an advantage over the other currently available second-generation antipsychotic LAIs. Simple constitution with sterile water and no requirement to refrigerate make storage and administration easier. Like all medications, there are always potential disadvantages to ALAI. There is a period of oral coverage, while not as long as for long-acting risperidone microspheres (RLAI), that is required. Care must be taken to review concomitant medications for the presence of metabolic inducers and inhibitors. One would also expect some patients to be sensitive to extrapyramidal symptoms, especially akathisia which is well documented in the oral preparation. All things considered, we welcome our new tool, ALAI, to our work-place and predict both clinical practice and post marketing analysis and studies will discover its true value.

In the United States, there are more than 35, 000 reported suicides with approximately 1, 800 of them being psychiatric inpatients. Staff perform intermittent or continuous observations in order to prevent such tragedies, but a study of 98 articles over time showed that 20% to 62% of suicides happened while inpatients were on an observation schedule. Reducing the instances of suicides of inpatients is a problem of critical importance to both patients and healthcare providers. In this paper, we introduce SHARE -A Self-Harm Activity Recognition Engine, which attempts to infer self-harming activities from sensing accelerometer data using smart devices worn on a subject's wrist. Preliminary classification accuracy of 80% was achieved using data acquired from 4 subjects performing a series of activities (both self-harming and not). The results, application, and proposed technology platform are discussed in-depth.

Background: Individuals with 22q11.2DS, a genetic subtype of Schizophrenia, respond as well to clozapine as those with other forms of Schizophrenia. It has been reported that serious and rare adverse events like seizures, and myocarditis have been associated with clozapine treatment in this population. To the best of our knowledge, the incidence of neuroleptic malignant syndrome (NMS) as an adverse effect of antipsychotic use in patients with this disorder has not yet been reported. Aim: In this article, we discuss a case of clozapine-induced NMS and subsequent re-challenge in a patient with 22q11.2DSassociated schizophrenia. The aim of this study is to accumulate scientific data about rare presentations, and serve as a major educational tool, and highlight the unique challenges faced when using clozapine in a patient with Di-George Syndrome. Methods: This is a descriptive case report of a patient encountered in the inpatient unit which includes retrospective review of the patient's electronic medical record and a literature review of antipsychotic medications-induced NMS. Conclusion: This study demonstrates a successful re-challenge with clozapine after the patient developed NMS and seizures during the initial treatment and also highlights how, in addition to drug level monitoring, considering pharmacogenetic testing early in treatment might help minimize adverse drug reactions in individuals with known genetic disorders such as 22q11.2DS.

Background: Frontotemporal dementia (FTD) is characterized by progressive deterioration in behaviors, executive function and/or language. The behavioral variant (Bv) is characterized by disinhibition and obsessive/compulsive behaviors. These symptoms are sometimes resistant to medications. This series examines patients suffering with treatment-resistant Bv-FTD who were prescribed cannabinoid and related compounds for other indications. Case presentation: Three FTD cases from a dementia clinic were identified. These patients had disability due to behavior despite typical pharmacologic management. These patients were prescribed marijuana for comorbidities (anxiety, insomnia and pain). In all cases, use of cannabinoid products showed significant improvements in behavior and in the primary indication for prescription. Conclusion: Review of these cases demonstrates potential for the use of cannabinoids in the management of treatment-resistant Bv-FTD.

Antipsychotics have long been the mainstay for the treatment of schizophrenia and other psychotic disorders. Long-acting injectables (LAI) of antipsychotics-provided once every two weeks to once every three months-promise to reduce the incidence of nonadherence. ARISTADA(™) (aripiprazole lauroxil; ALLAI) extended-release injectable suspension was approved by the U.S. Food and Drug Administration in October 2015 for the treatment of schizophrenia, and is the newest entrant in the LAI market. ALLAI is available as a single-use, pre-filled syringe, can be started in three different dosages, and also has the option of every six-week dosing. Treatment with oral aripiprazole is recommended for the first twenty-one days after the first ALLAI injection, which is a potential disadvantage. Adverse effects include sensitivity to extrapyramidal symptoms, especially akathisia, which is well documented in other aripiprazole preparations. There is no available data comparing ALLAI to other antipsychotics, and more head-to-head trials comparing different LAI formulations are needed. Based on the available data, ALLAI is an effective and safe option for treatment of schizophrenia. Further studies and post-marketing data will provide better understanding of this formulation.