Person:

Torous, John

Schizophrenia is a highly disabling disorder whose causes remain to be better understood, and treatments have to be improved. However, several recent advances have been made in diagnosis, etiopathology, and treatment. Whereas reliability of diagnosis has improved with operational criteria, including Diagnostic and Statistical Manual of Mental Disorders, (DSM) Fifth Edition, validity of the disease boundaries remains unclear because of substantive overlaps with other psychotic disorders. Recent emphasis on dimensional approaches and translational bio-behavioral research domain criteria may eventually help move toward a neuroscience-based definition of schizophrenia. The etiology of schizophrenia is now thought to be multifactorial, with multiple small-effect and fewer large-effect susceptibility genes interacting with several environmental factors. These factors may lead to developmentally mediated alterations in neuroplasticity, manifesting in a cascade of neurotransmitter and circuit dysfunctions and impaired connectivity with an onset around early adolescence. Such etiopathological understanding has motivated a renewed search for novel pharmacological as well as psychotherapeutic targets. Addressing the core features of the illness, such as cognitive deficits and negative symptoms, and developing hypothesis-driven early interventions and preventive strategies are high-priority goals for the field. Schizophrenia is a severe, chronic mental disorder and is among the most disabling disorders in all of medicine. It is estimated by the National Institute of Mental Health (NIMH) that 2.4 million people over the age of 18 in the US suffer from schizophrenia. This illness typically begins in adolescence and derails the formative goals of school, family, and work, leading to considerable suffering and disability and reduced life expectancy by about 20 years. Treatment outcomes are variable, and some people are successfully treated and reintegrated (i.e. go back to work). Despite the effort of many experts in the field, however, schizophrenia remains a chronic relapsing and remitting disorder associated with significant impairments in social and vocational functioning and a shortened lifespan. Comprehensive treatment entails a multi-modal approach, including psychopharmacology, psychosocial interventions, and assistance with housing and financial sustenance. Research to date suggests a network of genetic, neural, behavioral, and environmental factors to be responsible for its development and course. This article aims to summarize and explain recent advancements in research on schizophrenia, to suggest how these recent discoveries may lead to a better understanding and possible further development of effective therapies, and to highlight the paradigm shifts that have taken place in our understanding of the diagnosis, etiopathology, and treatment.

Background: There are over 165,000 mHealth apps currently available to patients, but few have undergone an external quality review. Furthermore, no standardized review method exists, and little has been done to examine the consistency of the evaluation systems themselves. Objective: We sought to determine which measures for evaluating the quality of mHealth apps have the greatest interrater reliability. Methods: We identified 22 measures for evaluating the quality of apps from the literature. A panel of 6 reviewers reviewed the top 10 depression apps and 10 smoking cessation apps from the Apple iTunes App Store on these measures. Krippendorff’s alpha was calculated for each of the measures and reported by app category and in aggregate. Results: The measure for interactiveness and feedback was found to have the greatest overall interrater reliability (alpha=.69). Presence of password protection (alpha=.65), whether the app was uploaded by a health care agency (alpha=.63), the number of consumer ratings (alpha=.59), and several other measures had moderate interrater reliability (alphas>.5). There was the least agreement over whether apps had errors or performance issues (alpha=.15), stated advertising policies (alpha=.16), and were easy to use (alpha=.18). There were substantial differences in the interrater reliabilities of a number of measures when they were applied to depression versus smoking apps. Conclusions: We found wide variation in the interrater reliability of measures used to evaluate apps, and some measures are more robust across categories of apps than others. The measures with the highest degree of interrater reliability tended to be those that involved the least rater discretion. Clinical quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability. Subsequent research is needed to determine consistent means for evaluating the performance of apps. Patients and clinicians should consider conducting their own assessments of apps, in conjunction with evaluating information from reviews.

Mobile and connected devices like smartphones and wearable sensors can facilitate the collection of novel naturalistic and longitudinal data relevant to psychiatry at both the personal and population level. The National Institute of Mental Health’s Research Domain Criteria framework offers a useful roadmap to organize, guide and lead new digital phenotyping data towards research discoveries and clinical advances.

Background: While clinical evidence for the efficacy of brain training remains in question, numerous smartphone applications (apps) already offer brain training directly to consumers. Little is known about why consumers choose to download these apps, how they use them, and what benefits they perceive. Given the high rates of smartphone ownership in those with internet access and the younger demographics, we chose to approach this question first with a general population survey that would capture primarily this demographic. Method: We conducted an online internet-based survey of the US population via mTurk regarding their use, experience, and perceptions of brain training apps. There were no exclusion criteria to partake although internet access was required. Respondents were paid 20 cents for completing each survey. The survey was offered for a 2-week period in September 2015. Results: 3125 individuals completed the survey and over half of these were under age 30. Responses did not significantly vary by gender. The brain training app most frequently used was Lumosity. Belief that a brain-training app could help with thinking was strongly correlated with belief it could also help with attention, memory, and even mood. Beliefs of those who had never used brain-training apps were similar to those who had used them. Respondents felt that data security and lack of endorsement from a clinician were the two least important barriers to use. Discussion: Results suggest a high level of interest in brain training apps among the US public, especially those in younger demographics. The stability of positive perception of these apps among app-naïve and app-exposed participants suggests an important role of user expectations in influencing use and experience of these apps. The low concern about data security and lack of clinician endorsement suggest apps are not being utilized in clinical settings. However, the public’s interest in the effectiveness of apps suggests a common theme with the scientific community’s concerns about direct to consumer brain training programs.

Background: Despite growing interest in mobile mental health and utilization of smartphone technology to monitor psychiatric symptoms, there remains a lack of knowledge both regarding patient ownership of smartphones and their interest in using such to monitor their mental health. Objective: To provide data on psychiatric outpatients’ prevalence of smartphone ownership and interest in using their smartphones to run applications to monitor their mental health. Methods: We surveyed 320 psychiatric outpatients from four clinics around the United States in order to capture a geographically and socioeconomically diverse patient population. These comprised a state clinic in Massachusetts (n=108), a county clinic in California (n=56), a hybrid public and private clinic in Louisiana (n=50), and a private/university clinic in Wisconsin (n=106). Results: Smartphone ownership and interest in utilizing such to monitor mental health varied by both clinic type and age with overall ownership of 62.5% (200/320), which is slightly higher than the average United States’ rate of ownership of 58% in January 2014. Overall patient interest in utilizing smartphones to monitor symptoms was 70.6% (226/320). Conclusions: These results suggest that psychiatric outpatients are interested in using their smartphones to monitor their mental health and own the smartphones capable of running mental healthcare related mobile applications.

Background: While medical students and residents may be utilizing websites as online learning resources, medical trainees and educators now have the opportunity to create such educational websites and digital tools on their own. However, the process and theory of building educational websites for medical education have not yet been fully explored. Objective: To understand the opportunities, barriers, and process of creating a novel medical educational website. Methods: We created a pilot psychiatric educational website to better understand the options, opportunities, challenges, and processes involved in the creation of a psychiatric educational website. We sought to integrate visual and interactive Web design elements to underscore the potential of such Web technology. Results: A pilot website (PsychOnCall) was created to demonstrate the potential of Web technology in medical and psychiatric education. Conclusions: Creating an educational website is now technically easier than ever before, and the primary challenge no longer is technology but rather the creation, validation, and maintenance of information for such websites as well as translating text-based didactics into visual and interactive tools. Medical educators can influence the design and implementation of online educational resources through creating their own websites and engaging medical students and residents in the process.

Background: There is increasing interest in using electronic behavioral interventions as well as mobile technologies such as smartphones for improving the care of chronic disabling diseases such as migraines. However, less is known about the current clinical evidence for the feasibility and effectiveness of such behavioral interventions. Objective: To review the published literature of behavioral interventions for primary headache disorders delivered by electronic means suitable for use outside of the clinician’s office. Methods: An electronic database search of PubMed, PsycINFO, and Embase was conducted through December 11, 2015. All eligible studies were systematically reviewed to examine the modality in which treatment was delivered (computer, smartphone, watch and other), types of behavioral intervention delivered (cognitive behavioral therapy [CBT], biofeedback, relaxation, other), the headache type being treated, duration of treatment, adherence, and outcomes obtained by the trials to examine the overall feasibility of electronic behavioral interventions for headache. Results: Our search produced 291 results from which 23 eligible articles were identified. Fourteen studies used the internet via the computer, 2 used Personal Digital Assistants, 2 used CD ROM and 5 used other types of devices. None used smartphones or wearable devices. Four were pilot studies (N ≤ 10) which assessed feasibility. For the behavioral intervention, CBT was used in 11 (48 %) of the studies, relaxation was used in 8 (35 %) of the studies, and biofeedback was used in 5 (22 %) of the studies. The majority of studies (14/23, 61 %) used more than one type of behavioral modality. The duration of therapy ranged from 4–8 weeks for CBT with a mean of 5.9 weeks. The duration of other behavioral interventions ranged from 4 days to 60 months. Outcomes measured varied widely across the individual studies. Conclusions: Despite the move toward individualized medicine and mHealth, the current literature shows that most studies using electronic behavioral intervention for the treatment of headache did not use mobile devices. The studies examining mobile devices showed that the behavioral interventions that employed them were acceptable to patients. Data are limited on the dose required, long term efficacy, and issues related to the security and privacy of this health data. This study was registered at the PROSPERO International Prospective Register of Systematic Reviews (CRD42015032284) (Prospero, 2015).

“Nothing is more difficult than to ascertain the length of time that a maniacal patient can exist without sleep.”—Dr. Sutherland (Br J Psychiatry 7(37):1–19, 1861). Dr. Sutherland’s patient was suffering from an acute manic episode, which today is called bipolar illness. 150 years later, we continue to struggle with the same challenges in ascertaining accurate symptoms from patients. In era of new digital tools, the quantified self-movement, and precision medicine, we can ask the question: Can we advance understanding and treatment for bipolar illness beyond asking the same questions as in 1861?