Bladder Point-of-Care Ultrasound: A Time Saver in the Pediatric Emergency Department.

BACKGROUND: Pediatric patients undergoing transabdominal pelvic ultrasound require a full bladder as an acoustic window. Patients are typically relied upon to subjectively identify bladder fullness, but inaccurate reporting often leads to delays in test results, diagnosis, and treatment. OBJECTIVES: Our aim was to objectively evaluate bladder fullness by comparing the height of the bladder to the height of the uterus on point-of-care ultrasound (POCUS). Our hypothesis was that this method would result in faster time to imaging and decrease emergency department length of stay (ED LOS). METHODS: Bladder fullness was assessed using POCUS every 30 min until the bladder was full. If the height of the bladder was equal to or greater than the height of the uterus in the sagittal view, the bladder was considered full. The POCUS group was compared with a control group that relied solely on patients' self-identified bladder fullness. RESULTS: Females aged 8-18 years old with pelvic pain in the pediatric ED were included in the study. Forty POCUS patients were compared with a control group of 105 patients. The POCUS group demonstrated a decrease in time to pelvic imaging by 38.7 min (95% confidence interval -59.2 to -18.2; p < 0.0001) and a decrease in LOS by 49.2 min (95% CI -89.7 to -8.61; p = 0.004). There was poor overall agreement on bladder fullness between patient's subjective sensation and POCUS (k = 0.04). CONCLUSION: POCUS to evaluate bladder fullness by comparing the height of the bladder with the height of the uterus reduces time to pelvic imaging and ED LOS.

Using Facebook to Reach People Who Experience Auditory Hallucinations.

BACKGROUND: Auditory hallucinations (eg, hearing voices) are relatively common and underreported false sensory experiences that may produce distress and impairment. A large proportion of those who experience auditory hallucinations go unidentified and untreated. Traditional engagement methods oftentimes fall short in reaching the diverse population of people who experience auditory hallucinations. OBJECTIVE: The objective of this proof-of-concept study was to examine the viability of leveraging Web-based social media as a method of engaging people who experience auditory hallucinations and to evaluate their attitudes toward using social media platforms as a resource for Web-based support and technology-based treatment. METHODS: We used Facebook advertisements to recruit individuals who experience auditory hallucinations to complete an 18-item Web-based survey focused on issues related to auditory hallucinations and technology use in American adults. We systematically tested multiple elements of the advertisement and survey layout including image selection, survey pagination, question ordering, and advertising targeting strategy. Each element was evaluated sequentially and the most cost-effective strategy was implemented in the subsequent steps, eventually deriving an optimized approach. Three open-ended question responses were analyzed using conventional inductive content analysis. Coded responses were quantified into binary codes, and frequencies were then calculated. RESULTS: Recruitment netted N=264 total sample over a 6-week period. Ninety-seven participants fully completed all measures at a total cost of $8.14 per participant across testing phases. Systematic adjustments to advertisement design, survey layout, and targeting strategies improved data quality and cost efficiency. People were willing to provide information on what triggered their auditory hallucinations along with strategies they use to cope, as well as provide suggestions to others who experience auditory hallucinations. Women, people who use mobile phones, and those experiencing more distress, were reportedly more open to using Facebook as a support and/or therapeutic tool in the future. CONCLUSIONS: Facebook advertisements can be used to recruit research participants who experience auditory hallucinations quickly and in a cost-effective manner. Most (58%) Web-based respondents are open to Facebook-based support and treatment and are willing to describe their subjective experiences with auditory hallucinations.

Cost of Implementing mHealth in Community Mental Health Settings: External Versus Internal Facilitation.

OBJECTIVE: This study aimed to compare the costs of two implementation models for the mobile health (mHealth) intervention FOCUS in community mental health settings. The external facilitation (EF) approach uses a hub-and-spoke model, in which a central specialist provides support to clinicians and clients at multiple agencies. With the internal facilitation (IF) approach, frontline clinical staff at each center are trained to serve as their organization's local specialists. METHODS: Financial and economic cost data were collected in the context of a hybrid type 3 effectiveness-implementation trial by using a mixed-methods, top-down expenditure analysis with microcosting approaches. The analysis compared the incremental costs of both models and the costs of successfully engaging clients (N=210) at 20 centers. Costs were characterized as start-up or recurrent (personnel, supplies, contracted services, and indirect costs). RESULTS: The average annual financial cost per site was $23,517 for EF and $19,118 for IF. EF yielded more FOCUS users at each center, such that the average monthly financial costs were lower for EF ($167 per client [N=129]) than for IF ($177 per client [N=81]). When using a real-world scenario based on economic costs and a lower organizational indirect rate, the average monthly cost per client was $73 for EF and $59 for IF. Both models reflected substantial cost reductions (about 50%) relative to a previous deployment of FOCUS in a clinical trial. CONCLUSIONS: Compared with IF, EF yielded more clients who received mHealth at community mental health centers and had comparable or lower costs.

Supporting psychosis research, implementation, and training through an academic intermediary-purveyor organization.

Intermediary-purveyor organizations (IPOs) are a type of dissemination support system that are intended to enhance the adoption and sustainment of empirically supported treatments (ESTs) by deploying empirically supported strategies to remediate implementation challenges. Despite the recent proliferation of government-funded IPOs for other psychiatric populations, IPOs that can redress the substantial science-to-practice gap among clients who experience psychotic disorders are not well documented. This article provides an overview of an IPO in an R1 academic medical center whose mission is to enhance access to evidence-based interventions for individuals who have or are at risk for a psychotic disorder. The article spotlights the functions of an IPO and illustrates these functions with a use case, cognitive behavioral therapy for psychosis. We highlight IPO-led activities related to cognitive behavioral therapy for psychosis purveyance, professional development, quality improvement, public awareness education and training, research and evaluation, as well as program and policy development. Finally, we address the advantages and disadvantages of establishing IPOs of this nature in academic medical centers, the importance of academic-community partnerships in advancing EST implementation, and present considerations for replication. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Use of pediatric trauma simulations to facilitate exposure to pediatric trauma resuscitations during training.

BACKGROUND: Pediatric traumas are often high-acuity but are low-frequency compared to adult trauma activations. This is reflected in the relatively limited experience with these events during training. Although some principles of trauma resuscitation are similar between adults and children, there are also important differences in physiology, injury patterns, and presentation. Therefore, simulation can be used to supplement trainee exposure and enhance their ability to respond to these high-stakes events. METHODS: We developed a multidisciplinary pediatric trauma resuscitation simulation curriculum to increase exposure to pediatric traumas at our institution. The intervention includes monthly sessions in the pediatric resuscitation bays, during which multidisciplinary teams complete 2 full pediatric trauma resuscitation simulations. This is supplemented with formal debriefing, simulation-specific teaching, and standardized trauma cognitive aids. The comprehensiveness of trauma evaluations and resuscitation efforts are evaluated using our institutional structured trauma resuscitation observation tool, and post-simulation surveys are used to assess the impact of the teaching interventions. RESULTS: Nine simulation sessions were conducted with more than 100 participants, including surgical residents, emergency medicine residents, nursing staff, respiratory therapists, and medical students. Completeness of resuscitation efforts improved from 55% to 82% (P < .01) between initial and repeat simulations. Surveyed participants reported improvement in overall team performance on the Team Emergency Assessment Measure (P < .01). CONCLUSION: Implementing a multidisciplinary pediatric trauma simulation curriculum with structured teaching interventions and standardized trauma scripts promotes teamwork and strengthens trainees' ability to conduct comprehensive evaluations required for high-acuity pediatric traumas.

Expanding the Reach of Research: Quantitative Evaluation of a Web-Based Approach for Remote Recruitment of People Who Hear Voices.

BACKGROUND: Similar to other populations with highly stigmatized medical or psychiatric conditions, people who hear voices (ie, experience auditory verbal hallucinations [AVH]) are often difficult to identify and reach for research. Technology-assisted remote research strategies reduce barriers to research recruitment; however, few studies have reported on the efficiency and effectiveness of these approaches. OBJECTIVE: This study introduces and evaluates the efficacy of technology-assisted remote research designed for people who experience AVH. METHODS: Our group developed an integrated, automated and human complementary web-based recruitment and enrollment apparatus that incorporated Google Ads, web-based screening, identification verification, hybrid automation, and interaction with live staff. We examined the efficacy of that apparatus by examining the number of web-based advertisement impressions (ie, number of times the web-based advertisement was viewed); clicks on that advertisement; engagement with web-based research materials; and the extent to which it succeeded in representing a broad sample of individuals with AVH, assessed through the self-reported AVH symptom severity and demographic representativeness (relative to the US population) of the sample recruited. RESULTS: Over an 18-month period, our Google Ads advertisement was viewed 872,496 times and clicked on 11,183 times. A total amount of US $4429.25 was spent on Google Ads, resulting in 772 individuals who experience AVH providing consent to participate in an entirely remote research study (US $0.40 per click on the advertisement and US $5.73 per consented participant) after verifying their phone number, passing a competency screening questionnaire, and providing consent. These participants reported high levels of AVH frequency (666/756, 88.1% daily or more), distress (689/755, 91.3%), and functional interference (697/755, 92.4%). They also represented a broad sample of diversity that mirrored the US population demographics. Approximately one-third (264/756, 34.9%) of the participants had never received treatment for their AVH and, therefore, were unlikely to be identified via traditional clinic-based research recruitment strategies. CONCLUSIONS: Web-based procedures allow for time saving, cost-efficient, and representative recruitment of individuals with AVH and can serve as a model for future studies focusing on hard-to-reach populations.

Perspectives on Mobile Health Versus Clinic-Based Group Interventions for People With Serious Mental Illnesses: A Qualitative Study.

OBJECTIVE: This study built on research comparing a mobile health intervention (FOCUS) and a clinic-based intervention (Wellness Recovery Action Planning [WRAP]) for self-management of serious mental illnesses. Qualitative interviews were conducted to provide additional insight into engagement and satisfaction and augment understanding of clinical outcomes. METHODS: Individuals (N=31) with serious mental illness participating in a comparative effectiveness trial were interviewed. Interviewees were sampled purposively for a range of engagement with the interventions. Interviews inquired into experiences with the interventions and were 45-60 minutes long, audio recorded, and transcribed. Researchers developed qualitative codes based on the research aims, interview domains, and inductively derived categories, aggregating data by code and producing analytic memos to distill main findings. RESULTS: Both FOCUS and WRAP participants described gaining new information about mental illness and new skills for managing symptoms. FOCUS participants emphasized the intervention's accessibility, and WRAP participants highlighted the importance of community and shared experiences. FOCUS participants commenced treatment at higher rates, compared with WRAP participants, which may have been related to the strongly negative views of group interventions expressed by some WRAP participants. FOCUS was generally enthusiastically received. The comparable clinical outcomes of the interventions were reflected in narratives detailing the positive impact of the interventions. CONCLUSIONS: Interviews provided evidence that mobile health and clinic-based illness self-management interventions were well received and offered opportunities to learn new illness management skills. Findings support expanding the range of services and supports for persons with serious mental illness to include traditional and technology-based approaches.

Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia.

Schizophrenia is a severe and complex psychiatric disorder with heterogeneous and dynamic multi-dimensional symptoms. Behavioral rhythms, such as sleep rhythm, are usually disrupted in people with schizophrenia. As such, behavioral rhythm sensing with smartphones and machine learning can help better understand and predict their symptoms. Our goal is to predict fine-grained symptom changes with interpretable models. We computed rhythm-based features from 61 participants with 6,132 days of data and used multi-task learning to predict their ecological momentary assessment scores for 10 different symptom items. By taking into account both the similarities and differences between different participants and symptoms, our multi-task learning models perform statistically significantly better than the models trained with single-task learning for predicting patients' individual symptom trajectories, such as feeling depressed, social, and calm and hearing voices. We also found different subtypes for each of the symptoms by applying unsupervised clustering to the feature weights in the models. Taken together, compared to the features used in the previous studies, our rhythm features not only improved models' prediction accuracy but also provided better interpretability for how patients' behavioral rhythms and the rhythms of their environments influence their symptom conditions. This will enable both the patients and clinicians to monitor how these factors affect a patient's condition and how to mitigate the influence of these factors. As such, we envision that our solution allows early detection and early intervention before a patient's condition starts deteriorating without requiring extra effort from patients and clinicians.

Mobile RDoC: Using Smartphones to Understand the Relationship Between Auditory Verbal Hallucinations and Need for Care.

OBJECTIVE: Auditory verbal hallucinations (AVH) are common in multiple clinical populations but also occur in individuals who are otherwise considered healthy. Adopting the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, the aim of the current study was to integrate a variety of measures to evaluate whether AVH experience varies across clinical and nonclinical individuals. METHODS: A total of 384 people with AVH from 41 US states participated in the study; 295 participants (77%) who received inpatient, outpatient, or combination treatments for AVH and 89 participants (23%) who never received care. Participants used a multi-modal smartphone data collection system to report on their AVH experiences and co-occurring psychological states multiple times daily, over 30 days. In parallel, smartphone sensors recorded their physical activity, geolocation, and calling and texting behavior continuously. RESULTS: The clinical sample experienced AVH more frequently than the nonclinical group and rated their AVH as significantly louder and more powerful. They experienced more co-occurring negative affect and were more socially withdrawn, spending significantly more time at home and significantly less time near other people. Participants with a history of inpatient care also rated their AVH as infused with significantly more negative content. The groups did not differ in their physical activity or use of their smartphones for digital communication. CONCLUSION: Smartphone-assisted remote data collection revealed real-time/real-place phenomenological, affective, and behavioral differences between clinical and nonclinical samples of people who experience AVH. The study provided strong support for the application of RDoC-informed approaches in psychosis research.

Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early warning signs of impending symptomatic relapses would allow clinicians to intervene before the patient's condition worsens. OBJECTIVE: In this study, we aim to create the first models, exclusively using passive sensing data from a smartphone, to predict behavioral anomalies that could indicate early warning signs of a psychotic relapse. METHODS: Data used to train and test the models were collected during the CrossCheck study. Hourly features derived from smartphone passive sensing data were extracted from 60 patients with SSDs (42 nonrelapse and 18 relapse >1 time throughout the study) and used to train models and test performance. We trained 2 types of encoder-decoder neural network models and a clustering-based local outlier factor model to predict behavioral anomalies that occurred within the 30-day period before a participant's date of relapse (the near relapse period). Models were trained to recreate participant behavior on days of relative health (DRH, outside of the near relapse period), following which a threshold to the recreation error was applied to predict anomalies. The neural network model architecture and the percentage of relapse participant data used to train all models were varied. RESULTS: A total of 20,137 days of collected data were analyzed, with 726 days of data (0.037%) within any 30-day near relapse period. The best performing model used a fully connected neural network autoencoder architecture and achieved a median sensitivity of 0.25 (IQR 0.15-1.00) and specificity of 0.88 (IQR 0.14-0.96; a median 108% increase in behavioral anomalies near relapse). We conducted a post hoc analysis using the best performing model to identify behavioral features that had a medium-to-large effect (Cohen d>0.5) in distinguishing anomalies near relapse from DRH among 4 participants who relapsed multiple times throughout the study. Qualitative validation using clinical notes collected during the original CrossCheck study showed that the identified features from our analysis were presented to clinicians during relapse events. CONCLUSIONS: Our proposed method predicted a higher rate of anomalies in patients with SSDs within the 30-day near relapse period and can be used to uncover individual-level behaviors that change before relapse. This approach will enable technologists and clinicians to build unobtrusive digital mental health tools that can predict incipient relapse in SSDs.

Life with FOCUS: A qualitative evaluation of the impact of a smartphone intervention on people with serious mental illness.

OBJECTIVE: A growing body of literature indicates that mobile health (mHealth) interventions that utilize smartphones for illness management are feasible, acceptable, and clinically promising. In this study, we examine how individuals with serious mental illness use a mHealth intervention-FOCUS-to self-manage their illnesses. Additionally, we explored participant perceptions of the intervention's impact on their subjective illness experience. METHOD: We analyzed qualitative data from 30 individuals with serious mental illness who participated in 1 of 2 community-based, 3-month trials of FOCUS. In Study 1, weekly calls were conducted by a mHealth specialist to facilitate and enhance intervention use. In Study 2, researchers conducted qualitative interviews to gather detailed perspectives of intervention use. Data were sampled from the weekly call notes and qualitative interviews and analyzed using a thematic and collaborative approach. RESULTS: Thematic analyses revealed 6 recurring themes. Three themes emerged in regard to participants' ongoing daily use of FOCUS: "back-up" support, symptom management, and self-awareness. Another 3 themes emerged related to the intervention's impact on participants' recovery processes: acceptance of symptoms, motivation and supporting positive outlook. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: This qualitative study offers insight into how individuals with serious mental illness made use of a mHealth intervention designed to support illness self-management. Our findings suggest that individuals may benefit differently from mHealth interventions depending on where they are in the recovery process. As mHealth interventions become increasingly popular in clinical settings, it is important to understand consumers' short-term and long-term benefits from these interventions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Relationships between smartphone social behavior and relapse in schizophrenia: A preliminary report.

Social dysfunction is a hallmark of schizophrenia. Social isolation may increase individuals' risk for psychotic symptom exacerbation and relapse. Monitoring and timely detection of shifts in social functioning are hampered by the limitations of traditional clinic-based assessment strategies. Ubiquitous mobile technologies such as smartphones introduce new opportunities to capture objective digital indicators of social behavior. The goal of this study was to evaluate whether smartphone-collected digital measures of social behavior can provide early indication of relapse events among individuals with schizophrenia. Sixty-one individuals with schizophrenia with elevated risk for relapse were given smartphones with the CrossCheck behavioral sensing system for a year of remote monitoring. CrossCheck leveraged the device's microphone, call record, and text messaging log to capture digital socialization data. Relapse events including psychiatric hospitalizations, suicidal ideation, and significant psychiatric symptom exacerbations were recorded by trained assessors. Exploratory mixed effects models examined relationships of social behavior to relapse, finding that reductions in number and duration of outgoing calls, as well as number of text messages were associated with relapses. Number and duration of incoming phone calls and in-person conversations were not. Smartphone enabled social activity may provide an important metric in determining relapse risk in schizophrenia and provide access to sensitive, meaningful and ecologically valid data streams never before available in routine care.

Capturing behavioral indicators of persecutory ideation using mobile technology.

Most existing measures of persecutory ideation (PI) rely on infrequent in-person visits, and this limits their ability to assess rapid changes or real-world functioning. Mobile health (mHealth) technology may address these limitations. Little is known about passively sensed behavioral indicators associated with PI. In the current study, sixty-two participants with schizophrenia spectrum disorders completed momentary assessments of PI on a smartphone that also passively collected behavioral data for one year. Results suggested that PI was prevalent (n = 50, 82% of sample) but had infrequent incidence (25.2% of EMA responses). PI was also associated with changes in several passively sensed variables, including decreases in distance traveled (Mkilometers = -1.20, SD = 18.88), time spent in a vehicle (Mminutes = -4.15, SD = 49.59), length of outgoing phone calls (Mminutes = -0.79, SD = 13.13), time spent proximal to human speech (Mminutes = -6.26, SD = 153.03), and an increase in time sitting still (Mminutes = 4.04, SD = 94.69). The present study suggests changes associated with PI may be detectable by passive sensors, including reductions in moving or traveling, and time spent around others or in self-initiated phone conversations. These constructs might constitute risk for PI.

Video-based mobile health interventions for people with schizophrenia: Bringing the "pocket therapist" to life.

OBJECTIVE: To examine whether video-based mobile health (mHealth) interventions are feasible, acceptable, understandable, and engaging to people with schizophrenia. METHOD: This study used a mixed-methods design. Ten individuals with schizophrenia spectrum disorders were recruited for a month-long trial in which they used FOCUS-Audio/Video (FOCUS-AV), a smartphone system that offers video and written intervention options. Participants completed posttrial measures and engaged in semistructured interviews. FINDINGS: One participant dropped out. The remaining 9 participants used intervention videos successfully. Participants responded to 67% of system-delivered prompts to engage FOCUS-AV, and 52% of FOCUS-AV use was initiated by the users. On average, participants used interventions 6 days a week, 4 times daily. Participants used video functions an average of 28 times. They chose video over written interventions on 67% of the times they used on-demand functions but opted for written content 78% of the times they responded to prescheduled prompts. Clinician videos were rated as more personal, engaging, and helpful than written interventions. Video and written interventions were rated as equally usable and understandable. Written interventions were rated as more favorable in letting users proceed at their own pace. Similarly to what is seen in live therapy, the communication style and demeanor of clinicians depicted in intervention videos reportedly affected participants' experience with treatment. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Video-based mHealth may be a feasible, usable, acceptable, and highly engaging method for flexible delivery of interventions to people with schizophrenia using mobile technology. Producing intervention videos is more time-, labor-, and cost-intensive than generating written content, but participant feedback suggests that there may be added value in this approach. Additional research will determine whether video-based mHealth interventions lead to better, faster, or more sustainable clinical gains. (PsycINFO Database Record

Mobile Health (mHealth) Versus Clinic-Based Group Intervention for People With Serious Mental Illness: A Randomized Controlled Trial.

OBJECTIVE: mHealth approaches that use mobile phones to deliver interventions can help improve access to care for people with serious mental illness. The goal was to evaluate how mHealth performs against more traditional treatment. METHODS: A three-month randomized controlled trial was conducted of a smartphone-delivered intervention (FOCUS) versus a clinic-based group intervention (Wellness Recovery Action Plan [WRAP]). Participants were 163 clients, mostly from racial minority groups and with long-term, serious mental illness (schizophrenia or schizoaffective disorder, 49%; bipolar disorder, 28%; and major depressive disorder, 23%). Outcomes were engagement throughout the intervention; satisfaction posttreatment (three months); and improvement in clinical symptoms, recovery, and quality of life (assessed at baseline, posttreatment, and six months). RESULTS: Participants assigned to FOCUS were more likely than those assigned to WRAP to commence treatment (90% versus 58%) and remain fully engaged in eight weeks of care (56% versus 40%). Satisfaction ratings were comparably high for both interventions. Participants in both groups improved significantly and did not differ in clinical outcomes, including general psychopathology and depression. Significant improvements in recovery were seen for the WRAP group posttreatment, and significant improvements in recovery and quality of life were seen for the FOCUS group at six months. CONCLUSIONS: Both interventions produced significant gains among clients with serious and persistent mental illnesses who were mostly from racial minority groups. The mHealth intervention showed superior patient engagement and produced patient satisfaction and clinical and recovery outcomes that were comparable to those from a widely used clinic-based group intervention for illness management.

mHealth for mental health in the Middle East: Need, technology use, and readiness among Palestinians in the West Bank.

Palestinians in the West Bank are at heightened risk for mental health problems. Limited availability of clinicians and a host of geopolitical, topographical, and infrastructural challenges create significant regional barriers to clinic-based care. The objective of this study was to examine whether mHealth approaches that leverage mobile phones for remote mental health treatment may be viable alternatives. We surveyed 272 Palestinian adults in urban, rural, and refugee camp settings. Most participants (93.4%) reported owning mobile phones. The penetration of mobile devices was high across all study sites. Males and females did not differ in their access to this resource. Among mobile phone owners, 79.9% had smartphones, 32.2% had basic mobile phones, and 12.2% owned both. Respondents reported having reliable access to electricity (99.6%) and Wi-Fi (80.9%). Almost all mobile phone owners (99.6%) reported using social media such as Facebook, WhatsApp, or Twitter. When asked to estimate the prevalence of mental health problems in the region, 61.4% of participants reported that over half of the people in their communities struggled with depression, posttraumatic stress, or auditory hallucinations. Most participants indicated that they would personally be interested in mHealth for Mental Health options such as bi-directional texting with clinicians (68.8%), smartphone applications (66.5%), unidirectional support texts (64.7%), or web-based interventions (64.0%). Given the Palestinian populations' broad access to technology and technological infrastructure, need for care, and openness to engage in mobile interventions, mHealth should be considered a promising strategy for mental health services in the West Bank.

Use of Multimodal Technology to Identify Digital Correlates of Violence Among Inpatients With Serious Mental Illness: A Pilot Study.

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.

CrossCheck: Integrating self-report, behavioral sensing, and smartphone use to identify digital indicators of psychotic relapse.

OBJECTIVE: This purpose of this study was to describe and demonstrate CrossCheck, a multimodal data collection system designed to aid in continuous remote monitoring and identification of subjective and objective indicators of psychotic relapse. METHOD: Individuals with schizophrenia-spectrum disorders received a smartphone with the monitoring system installed along with unlimited data plan for 12 months. Participants were instructed to carry the device with them and to complete brief self-reports multiple times a week. Multimodal behavioral sensing (i.e., physical activity, geospatials activity, speech frequency, and duration) and device use data (i.e., call and text activity, app use) were captured automatically. Five individuals who experienced psychiatric hospitalization were selected and described for instructive purposes. RESULTS: Participants had unique digital indicators of their psychotic relapse. For some, self-reports provided clear and potentially actionable description of symptom exacerbation prior to hospitalization. Others had behavioral sensing data trends (e.g., shifts in geolocation patterns, declines in physical activity) or device use patterns (e.g., increased nighttime app use, discontinuation of all smartphone use) that reflected the changes they experienced more effectively. CONCLUSION: Advancements in mobile technology are enabling collection of an abundance of information that until recently was largely inaccessible to clinical research and practice. However, remote monitoring and relapse detection is in its nascence. Development and evaluation of innovative data management, modeling, and signal-detection techniques that can identify changes within an individual over time (i.e., unique relapse signatures) will be essential if we are to capitalize on these data to improve treatment and prevention. (PsycINFO Database Record

Mobile Behavioral Sensing for Outpatients and Inpatients With Schizophrenia.

OBJECTIVE: This study examined the feasibility, acceptability, and utility of behavioral sensing among individuals with schizophrenia. METHODS: Nine outpatients and 11 inpatients carried smartphones for two- or one-week periods, respectively. Device-embedded sensors (accelerometers, microphone, global positioning system, WiFi, and Bluetooth) collected behavioral data and ascertained the patients' location, activity, and exposure to human speech as they went about their day. Participants rated this approach by completing usability and acceptability measures. RESULTS: Sensing successfully captured individuals' activity, time spent proximal to human speech, and time spent in various locations. Participants felt comfortable using the sensing system (95%), and most were interested in receiving feedback (65%) and suggestions (65%). Approximately 20% reported that sensing made them upset. One-third of inpatients were concerned about their privacy, but no outpatients expressed this concern. CONCLUSIONS: Mobile behavioral sensing was a feasible, acceptable, and informative approach for data collection among outpatients and inpatients with schizophrenia.

Mobile health (mHealth) for mental health in Asia: objectives, strategies, and limitations.

Mobile technologies are transforming the way in which we interact with one another, access resources, find information, and conduct business around the world. Harnessing the capabilities of mobile technologies to support health care initiatives worldwide has developed into a new interdisciplinary field called mobile health (mHealth). In the current paper, we review the penetration of mobile technology in Asia, and consider the integration of mobile technologies into the study, diagnoses, and treatment of mental disorders in the region. We outline how mHealth programs could improve mental health literacy, provide greater access to mental health services, extend community-based outreach and engagement, support self-management of illness, and regulate medication distribution. We end with a consideration of the potential barriers and limitations of mHealth for mental health, including funding, language and literacy barriers, power supply considerations, data security, and privacy issues.