Objective The purpose of this study was to examine the feasibility, acceptability, and utility of behavioral sensing in individuals with schizophrenia. Methods Outpatients (N=9) and inpatients (N=11) carried smartphones for two or one week periods, respectively. Device-embedded sensors (i.e., accelerometers, microphone, GPS, WiFi, Bluetooth) collected behavioral and contextual data, as they went about their day. Participants completed usability/acceptability measures rating this approach. Results Sensing successfully captured individuals’ activity, time spent proximal to human speech, and time spent in different locations. Usability and acceptability ratings showed participants felt comfortable using the sensing system (95%), and that most would be interested in receiving feedback (65%) and suggestions (65%). Approximately 20% reported that sensing made them upset. A third of inpatients were concerned about their privacy, but no outpatients expressed this concern. Conclusions Mobile behavioral sensing is a feasible, acceptable, and informative approach for data collection in outpatients and inpatients with schizophrenia.

BackgroundAggression and violence on acute psychiatric inpatient units is extensive and leads to negative sequelae for staff and patients. With increasingly acute inpatient milieus due to shorter lengths of stay, inpatient staff is limited in training and time to be able to provide treatments. Mobile technology provides a new platform for offering treatment on such units, but it has not been tested for feasibility or usability in this particular setting.ObjectiveThe aim of this study was to examine the feasibility, usability, and acceptability of a brief mindfulness meditation mobile phone app intended to reduce anger and aggression in acute psychiatric inpatients with schizophrenia, schizoaffective disorder, or bipolar disorder, and a history of violence.MethodsParticipants were recruited between November 1, 2015 and June 1, 2016. A total of 13 inpatients at an acute care state hospital carried mobile phones for 1 week and were asked to try a commercially available mindfulness app called Headspace. The participants completed a usability questionnaire and engaged in a qualitative interview upon completion of the 7 days. In addition, measures of mindfulness, state and trait anger, and cognitive ability were administered before and after the intervention.ResultsOf the 13 enrolled participants, 10 used the app for the 7 days of the study and completed all measures. Two additional participants used the app for fewer than 7 days and completed all measures. All participants found the app to be engaging and easy to use. Most (10/12, 83%) felt comfortable using Headspace and 83% (10/12) would recommend it to others. All participants made some effort to try the app, with 6 participants (6/12, 50%) completing the first 10 10-minute “foundation” guided meditations.ConclusionsThis is the first known study of the use of a commercially available app as an intervention on acute psychiatric inpatient units. Acutely ill psychiatric inpatients at a state hospital found the Headspace app easy to use, were able to complete a series of meditations, and felt the app helped with anxiety, sleep, and boredom on the unit. There were no instances of an increase in psychotic symptoms reported and there were no episodes of aggression or violence noted in the record.

Structured shared decision making in mental health shows promise in supporting service user involvement in critical decision making and provides a process to open all treatment and service decisions to informed and respectful dialogue.

Background: Medicare Part D and the U.S. Department of Veterans Affairs (VA) use different approaches to manage prescription drug benefits, with implications for spending. Medicare relies on private plans with distinct formularies, whereas the VA administers its own benefit using a national formulary. Objective: To compare overall and regional rates of brand-name drug use among older adults with diabetes in Medicare and the VA. Design: Retrospective cohort. Setting: Medicare and the VA, 2008. Patients: 1 061 095 Medicare Part D beneficiaries and 510 485 veterans aged 65 years or older with diabetes. Measurements: Percentage of patients taking oral hypoglycemics, statins, and angiotensin-converting enzyme (ACE) inhibitors or angiotensin-receptor blockers (ARBs) who filled brand-name drug prescriptions and percentage of patients taking long-acting insulins who filled analogue prescriptions. Sociodemographic- and health status–adjusted hospital referral region (HRR) brand-name drug use was compared, and changes in spending were calculated if use of brand-name drugs in 1 system mirrored the other. Results: Brand-name drug use in Medicare was 2 to 3 times that in the VA: 35.3% versus 12.7% for oral hypoglycemics, 50.7% versus 18.2% for statins, 42.5% versus 20.8% for ACE inhibitors or ARBs, and 75.1% versus 27.0% for insulin analogues. Adjusted HRR-level brand-name statin use ranged (from the 5th to 95th percentiles) from 41.0% to 58.3% in Medicare and 6.2% to 38.2% in the VA. For each drug group, the 95th-percentile HRR in the VA had lower brand-name drug use than the 5th-percentile HRR in Medicare. Medicare spending in this population would have been $1.4 billion less if brand-name drug use matched that of the VA. Limitation: This analysis cannot fully describe the factors underlying differences in brand-name drug use. Conclusion: Medicare beneficiaries with diabetes use 2 to 3 times more brand-name drugs than a comparable group within the VA, at substantial excess cost. Primary Funding Source: U.S. Department of Veterans Affairs, National Institutes of Health, and Robert Wood Johnson Foundation.

Shared decision making (SDM) is a health communication approach focusing on patient-clinician interactions around treatment decisions, with the goals of improving clinical and functional outcomes and providing personalized care. 1 The fundamental principles of SDM involve (1) eliminating power asymmetries between clinician and patient; (2) acknowledging that there are at least 2 expert participants: a patient having livedexperience expertise, a clinician having professional expertise, and sometimes a family member 2 ; (3) eliciting patient preferences for their involvement in the decisionmaking (autonomously, conjointly with clinician input, letting clinician make decisions) and eliciting the patient's specific values that could guide the decision (eg, reducing medication adverse effects); (4) discussing at least 2 treatment options (eg, taking, tapering, or stopping antipsychotic medications); ( 5) making a decision that aligns with the patient's goals, preferences, and values that also makes clear the risks involved in particular decisions 3 ; and (6) accepting that the patient's choice of treatment plan may differ from the clinician's recommendation. SDM has been endorsed as the gold standard of patient-clinician interaction in preferencebased care by the National Academy of Medicine in the US and the National Institute for Health and Care Excellence in the UK. Studies in the last decade of individuals with serious mental illness (SMI) demonstrating the feasibility of using SDM, and showing the potential for improved outcomes, support the recent acknowledgment of SDM as an essential practice by the American Psychiatric Association 4 and the Substance Abuse and Mental Health Services Administration.Despite the potential contribution of SDM in mental health, it has yet to be successfully adopted for use in routine psychiatric care, especially for discussing treatment with individuals with SMI. Several patient-, clinician-, and system/policy-related barriers impeding SDM implementation among individuals with SMI have been identified 5 but only partly addressed. For example, a positive shift toward SDM has occurred at the system/ policy level, with greater acceptance of the notion of SDM in psychiatry by the American Psychiatric Association 4 and Substance Abuse and Mental Health Services Administration. At the patient level, recent systematic reviews indicate increased development and testing of patient decision aids and SDM interventions. Clinician-related barriers to SDM in psychiatry, however, have received far less empirical investigation. Because psychiatrists are an essential part of SDM, the purpose of this Viewpoint is to discuss critical, yet-tobe-addressed, clinician-related barriers that serve as the "elephant in the room," impeding extensive implementation of SDM in psychiatry.

A collaborative approach to reducing polypharmacy may reverse the trend to add medications during hospitalization.

Objective The study examined multimodal technologies to identify correlates of violence among inpatients with serious mental illness. Methods Twenty-eight high-risk inpatients were provided with smartphones adapted for data collection. Participants recorded their thoughts and behaviors by using self-report software. Sensors embedded in each device (microphone and accelerometers) and throughout the inpatient unit (Bluetooth beacons) captured patients’ activity and location. Results Self-reported delusions were associated with violent ideation (odds ratio [OR]=3.08), damaging property (OR=8.24), and physical aggression (OR=12.39). Alcohol and cigarette cravings were associated with violent ideation (OR=5.20 and OR=6.08, respectively), damaging property (OR=3.71 and OR=4.26, respectively), threatening others (OR=3.62 and OR=3.04, respectively), and physical aggression (OR=6.26, and OR=8.02, respectively). Drug cravings were associated with violent ideation (OR=2.76) and damaging property (OR=5.09). Decreased variability in physical activity and noisy ward conditions were associated with violent ideation (OR=.71 and OR=2.82, respectively). Conclusions Identifiable digital correlates may serve as indicators of increased risk of violence.

The similar efficacies of currently available antipsychotic medications (other than clozapine) make them appropriate for preference-sensitive care; therefore, prescribing these medications is amenable to shared decision-making. In this conceptual article, we describe the current state of antipsychotic prescribing based on a review of the literature from recent landmark studies and updated prescribing guidelines. Recent literature and guidelines on schizophrenia treatment in the United States do not reveal strong endorsement of the idea of shared decision-making. We suggest methods for incorporating shared decision-making into antipsychotic prescribing in the future, with an emphasis on the use of information technology.