A Randomized Clinical Trial of Technology-Enhanced Family-Focused Therapy for Youth in the Early Stages of Mood Disorders.

Objective: Family-focused therapy (FFT) is associated with enhanced outcomes in youth with bipolar and depressive disorders, but has not been evaluated in conjunction with mobile health tools. In symptomatic adolescents whose parents had histories of mood disorders, we examined whether the effects of telehealth-based FFT were augmented by mobile health apps that emphasized mood tracking and family coping skills. Method: Participants (aged 13-19 years) had active mood symptoms and a parent with major depressive or bipolar disorder. Participants received 12 sessions in 18 weeks of telehealth FFT, with random assignment to (1) a mobile app (MyCoachConnect, MCC) that enabled mood tracking, reviews of session content, and text reminders to practice mood management and family communication skills (FFT-MCC); or (2) a mobile app that enabled mood tracking only (FFT-Track). Independent evaluators assessed youth every 9 weeks over 6 months on depressive symptoms (primary outcome), anxiety, and psychosocial functioning. Results: Participants (N = 65; mean age 15.8 ± 1.6 years) significantly improved in depressive symptoms over 6 months (F1,170 = 45.02, p < .0001; ή2 = 0.21, 95% CI = 0.11-0.31), but there were no effects of treatment condition or treatment by time interactions on depression scores. When secondary outcome measures were considered, the subgroup of youth with bipolar spectrum disorders showed greater improvements in anxiety and global functioning in FFT-MCC compared with FFT-Track. Conclusion: Youth in the early stages of mood disorder may benefit from FFT enhanced by mobile health apps. Collaborations between researchers and information technologists on mobile app design and user experience may lead to increases in engagement among adolescents. Clinical trial registration information: Technology Enhanced Family Treatment; https://clinicaltrials.gov/; NCT03913013.

Word usage in spontaneous speech as a predictor of depressive symptoms among youth at high risk for mood disorders.

BACKGROUND: We examined whether digital phenotyping of spontaneous speech, such as the use of specific word categories during speech samples, was associated with depressive symptoms in youth who were at familial and clinical risk for mood disorders. METHODS: Participants (ages 13-19) had active mood symptoms, mood instability, and at least one parent with bipolar or major depressive disorder. During a randomized trial of family-focused therapy, participants were instructed to make weekly calls to a central voice server and leave speech samples in response to automated prompts. We coded youths' speech samples with the Linguistic Inquiry and Word Count system and used machine learning to identify the combination of speech features that were most closely associated with the course of depressive symptoms over 18 weeks. RESULTS: A total of 253 speech samples were collected from 44 adolescents (mean age = 15.8 years; SD = 1.6) over 18 weeks. Speech containing affective processes, social processes, drives toward risk or reward, nonfluencies, and time orientation words were correlated with depressive symptoms at concurrent time periods (ps < 0.01). Machine learning analyses revealed that affective processes, nonfluencies, drives and risk words combined to most strongly predict changes in depressive symptoms over 18 weeks of treatment. LIMITATIONS: Study results were limited by the small sample and the exclusion of paralinguistic or contextual variables in analyzing speech samples. CONCLUSIONS: In youth at high risk for mood disorders, knowledge of speech patterns may inform prognoses during outpatient psychosocial treatment.

Reduced Environmental Stimulation Therapy (REST) in anxiety and depression: An experience sampling study.

Background: Reduced Environmental Stimulation Therapy (REST) is a behavioral intervention that systematically attenuates external sensory input to the nervous system. Previous studies have demonstrated acute anxiolytic and antidepressant effects of single sessions of REST in anxious individuals, however the duration and time course of these effects is unknown. In the current study, we used experience sampling and multiple sessions of REST to explore the time course of the anxiolytic and antidepressant effects over a 48-hour time period. Methods: 75 adults with anxiety and/or depression were randomized to complete 6 sessions of REST (either pool-REST, pool-REST preferred, or chair-REST). Post-REST effects were tracked using experience sampling on a smartphone with a ten-item survey administered at 6 time points for each session (i.e., immediately before and after REST and then 4, 8, 24, and 48 hours later). Using principal component analysis, responses to survey items at baseline were reduced to broad symptom clusters of anxiety, depression, and serenity and were utilized in linear mixed effects models to determine the magnitude and time course of post-REST effects. Results: REST was associated with significant decreases in anxiety and depression, and significant increases in serenity, with effects lasting for 48 hours. Repeated exposure to REST was associated with lower baseline levels of anxiety at later sessions. Conclusion: These initial findings suggest that the anxiolytic and antidepressant effects of REST persist for at least two days, and that repeated REST sessions may have additive effects on lowering anxiety-related symptoms. These findings could help to determine the optimal intervention frequency of REST and facilitate future investigations focused on the combination of REST with standard treatments for anxiety and depression.

Co-created Mobile Apps for Palliative Care Using Community-Partnered Participatory Research: Development and Usability Study.

BACKGROUND: Open design formats for mobile apps help clinicians and stakeholders bring their needs to direct, co-creative solutions. Palliative care for patients with advanced cancers requires intensive monitoring and support and remains an area in high need for innovation. OBJECTIVE: This study aims to use community-partnered participatory research to co-design and pretest a mobile app that focuses on palliative care priorities of clinicians and patients with advanced cancer. METHODS: In-person and teleconference workshops were held with patient and family stakeholders, researchers, and clinicians in palliative care and oncology. Question prompts, written feedback, semistructured interviews, and facilitated group discussions identified the core palliative care needs. Using Chorus, a no-code app-building platform, a mobile app was co-designed with the stakeholders. A pretest with 11 patients was conducted, with semistructured interviews of clinician and patient users for feedback. RESULTS: Key themes identified from the focus groups included needs for patient advocacy and encouragement, access to vetted information, patient-clinician communication support, and symptom management. The initial prototype, My Wellness App, contained a weekly wellness journal to track patient-reported symptoms, goals, and medication use; information on self-management of symptoms; community resources; and patient and caregiver testimonial videos. Initial pretesting identified value in app-based communication for clinicians, patients, and caregivers, with suggestions for improving user interface, feedback and presentation of symptom reports, and gamification and staff coordinators to support patient app engagement. CONCLUSIONS: The development of a mobile app using community-partnered participatory research is a low-technology and feasible intervention for palliative care. Iterative redesign and user interface expertise may improve implementation.

Visual mapping of body image disturbance in anorexia nervosa reveals objective markers of illness severity.

Body image disturbance (BID) is a core feature of eating disorders, for which there are few objective markers. We examined the feasibility of a novel digital tool, "Somatomap", to index BID related to anorexia nervosa (AN) severity. Fifty-five AN inpatients and 55 healthy comparisons (HC) outlined their body concerns on a 2-Dimensional avatar. Next, they indicated sizes/shapes of body parts for their current and ideal body using sliders on a 3-Dimensional avatar. Physical measurements of corresponding body parts, in cm, were collected for reference. We evaluated regional differences in BID using proportional z-scores to generate statistical body maps, and multivariate analysis of covariance to assess perceptual discrepancies for current body, ideal body, and body dissatisfaction. The AN group demonstrated greater regional perceptual inaccuracy for their current body than HC, greater discrepancies between their current and ideal body, and higher body dissatisfaction than HCs. AN body concerns localized disproportionately to the chest and lower abdomen. The number of body concerns and perceptual inaccuracy for individual body parts was strongly associated with Eating Disorder Examination Questionnaire (Global EDE-Q) scores across both groups. Somatomap demonstrated feasibility to capture multidimensional aspects of BID. Several implicit measures were significantly associated with illness severity, suggesting potential utility for identifying objective BID markers.

Using machine learning analyses of speech to classify levels of expressed emotion in parents of youth with mood disorders.

Expressed emotion (EE), a measure of attitudes among caregivers towards a patient with a psychiatric disorder, is a robust predictor of relapse across mood and psychotic disorders. Because the measurement of EE is time-intensive and costly, its use in clinical settings has been limited. In an effort to automate EE classification, we evaluated whether machine learning (ML) applied to lexical features of speech samples can accurately categorize parents as high or low in EE and in its subtypes (criticism, overinvolvement, and warmth). The sample was 123 parents of youth who had active mood symptoms and a family history of bipolar disorder. Using ML algorithms, we achieved 75.2-81.8% accuracy (sensitivities of ~0.7 and specificities of ~0.8) in classifying parents as high or low in EE and EE subtypes. Additionally, machine-derived EE classifications and observer-rated EE classifications had simiar relationships with youth mood symptoms, parental distress, and family conflict. Of note, criticism related to greater manic severity, parental distress, and family conflict. Study findings indicate that EE classification can be automated through lexical analysis and suggest potential for facilitating larger-scale applications in clinical settings. The results also provide initial indications of the digital phenotypes that underlie EE and its subtypes.

Mental Health Community and Health System Issues in COVID-19: Lessons from Academic, Community, Provider and Policy Stakeholders.

The coronavirus pandemic of 2019 (COVID-19) has created unprecedented changes to everyday life for millions of Americans due to job loss, school closures, stay-at-home orders and health and mortality consequences. In turn, physicians, academics, and policymakers have turned their attention to the public mental health toll of COVID-19. This commentary reporting from the field integrates perceptions of academic, community, health system, and policy leaders from state, county, and local levels in commenting on community mental health needs in the COVID-19 pandemic. Stakeholders noted the broad public health scope of mental health challenges while expressing concern about exacerbation of existing disparities in access and adverse social determinants, including for communities with high COVID-19 infection rates, such as African Americans and Latinos. They noted rapid changes toward telehealth and remote care, and the importance of understanding impacts of changes, including who may benefit or have limited access, with implications for future services delivery. Needs for expanded workforce and training in mental health were noted, as well as potential public health value of expanding digital resources tailored to local populations for enhancing resilience to stressors. The COVID-19 pandemic has led to changes in delivery of health care services across populations and systems. Concerns over the mental health impact of COVID-19 has enhanced interest in remote mental care delivery and preventive services, while being mindful of potential for enhanced disparities and needs to address social determinants of health. Ongoing quality improvement across systems can integrate lessons learned to enhance a public mental well-being.

Patient and Provider Cocreation of Mobile Texting Apps to Support Behavioral Health: Usability Study.

BACKGROUND: Mobile technologies hold potential for improving the quality of care and engagement of patients. However, there are considerable challenges in ensuring that technologies are relevant, useful, and engaging. While end users such as patients and providers are increasingly involved in the design of health technologies, there are limited examples of their involvement in directly creating technologies for their personal use. OBJECTIVE: We aim to evaluate the feasibility and acceptability of patients and providers creating mobile texting apps to support treatment goals. METHODS: In an 11-month usability study, we enrolled 4 providers and 28 patients in an intensive outpatient program for obsessive-compulsive disorder. Patients and providers created their own mobile texting apps using a visual app development platform. A subsample of 10 patients and 4 providers completed a usability measure. RESULTS: Participants created a total of 360 unique mobile text messages (1787 total messages sent). There were 4 types of messages identified, including personalized reminders, clinical exposures, interactive prompts, and encouraging/informational messages. A total of 9 out of 10 (90%) patients agreed that the messages were relevant to their recovery, and 8 out of 10 (80%) agreed that the messages were effective at helping complete treatment plans. CONCLUSIONS: Enabling patients and providers to cocreate apps for their own use by using a visual application platform is feasible and holds potential for increasing the relevance, sustainability, and effectiveness of digital health technologies.

Clinical state tracking in serious mental illness through computational analysis of speech.

Individuals with serious mental illness experience changes in their clinical states over time that are difficult to assess and that result in increased disease burden and care utilization. It is not known if features derived from speech can serve as a transdiagnostic marker of these clinical states. This study evaluates the feasibility of collecting speech samples from people with serious mental illness and explores the potential utility for tracking changes in clinical state over time. Patients (n = 47) were recruited from a community-based mental health clinic with diagnoses of bipolar disorder, major depressive disorder, schizophrenia or schizoaffective disorder. Patients used an interactive voice response system for at least 4 months to provide speech samples. Clinic providers (n = 13) reviewed responses and provided global assessment ratings. We computed features of speech and used machine learning to create models of outcome measures trained using either population data or an individual's own data over time. The system was feasible to use, recording 1101 phone calls and 117 hours of speech. Most (92%) of the patients agreed that it was easy to use. The individually-trained models demonstrated the highest correlation with provider ratings (rho = 0.78, p<0.001). Population-level models demonstrated statistically significant correlations with provider global assessment ratings (rho = 0.44, p<0.001), future provider ratings (rho = 0.33, p<0.05), BASIS-24 summary score, depression sub score, and self-harm sub score (rho = 0.25,0.25, and 0.28 respectively; p<0.05), and the SF-12 mental health sub score (rho = 0.25, p<0.05), but not with other BASIS-24 or SF-12 sub scores. This study brings together longitudinal collection of objective behavioral markers along with a transdiagnostic, personalized approach for tracking of mental health clinical state in a community-based clinical setting.

Preparedness and Community Resilience in Disaster-Prone Areas: Cross-Sectoral Collaborations in South Louisiana, 2018.

Objectives. To determine how community-based organizations (CBOs) define priorities for bolstering community resilience, challenges in addressing these priorities, and strategies to address challenges.Methods. The Community Resilience Learning Collaborative and Research Network (C-LEARN) is a multiphase study examining opportunities to improve community resilience to the threats of disaster and climate change in South Louisiana. Phase I of C-LEARN involved using the National Health Security Strategy and Implementation Plan for directed content analysis of key informant interviews with CBO representatives from 47 agencies within South Louisiana between February and May 2018.Results. CBO interviewees highlighted the importance of forging relationships and building trust through diverse cross-sector collaborations and partnerships before disasters. Such collaborations and partnerships were shown to tailor disaster response to the needs of particular communities and populations as well as address key challenges such as gaps in information, services, and resources.Conclusions. Our results encourage a culture of community resilience and community preparedness through partnerships and community-engaged strategies. C-LEARN will utilize the results of our interviews in the design of phase II of our agency-level coalition-building intervention.

A Novel Mobile Tool (Somatomap) to Assess Body Image Perception Pilot Tested With Fashion Models and Nonmodels: Cross-Sectional Study.

BACKGROUND: Distorted perception of one's body and appearance, in general, is a core feature of several psychiatric disorders including anorexia nervosa and body dysmorphic disorder and is operative to varying degrees in nonclinical populations. Yet, body image perception is challenging to assess, given its subjective nature and variety of manifestations. The currently available methods have several limitations including restricted ability to assess perceptions of specific body areas. To address these limitations, we created Somatomap, a mobile tool that enables individuals to visually represent their perception of body-part sizes and shapes as well as areas of body concerns and record the emotional valence of concerns. OBJECTIVE: This study aimed to develop and pilot test the feasibility of a novel mobile tool for assessing 2D and 3D body image perception. METHODS: We developed a mobile 2D tool consisting of a manikin figure on which participants outline areas of body concern and indicate the nature, intensity, and emotional valence of the concern. We also developed a mobile 3D tool consisting of an avatar on which participants select individual body parts and use sliders to manipulate their size and shape. The tool was pilot tested on 103 women: 65 professional fashion models, a group disproportionately exposed to their own visual appearance, and 38 nonmodels from the general population. Acceptability was assessed via a usability rating scale. To identify areas of body concern in 2D, topographical body maps were created by combining assessments across individuals. Statistical body maps of group differences in body concern were subsequently calculated using the formula for proportional z-score. To identify areas of body concern in 3D, participants' subjective estimates from the 3D avatar were compared to corresponding measurements of their actual body parts. Discrepancy scores were calculated based on the difference between the perceived and actual body parts and evaluated using multivariate analysis of covariance. RESULTS: Statistical body maps revealed different areas of body concern between models (more frequently about thighs and buttocks) and nonmodels (more frequently about abdomen/waist). Models were more accurate at estimating their overall body size, whereas nonmodels tended to underestimate the size of individual body parts, showing greater discrepancy scores for bust, biceps, waist, hips, and calves but not shoulders and thighs. Models and nonmodels reported high ease-of-use scores (8.4/10 and 8.5/10, respectively), and the resulting 3D avatar closely resembled their actual body (72.7% and 75.2%, respectively). CONCLUSIONS: These pilot results suggest that Somatomap is feasible to use and offers new opportunities for assessment of body image perception in mobile settings. Although further testing is needed to determine the applicability of this approach to other populations, Somatomap provides unique insight into how humans perceive and represent the visual characteristics of their body.

Depression Remission From Community Coalitions Versus Individual Program Support for Services: Findings From Community Partners in Care, Los Angeles, California, 2010-2016.

Objectives. To explore effects of coalitions (Community Engagement and Planning [CEP]) versus technical assistance (Resources for Services [RS]) for depression collaborative care and the effects of social determinants on long-term remission outcomes. Methods. We randomized 95 health care and community programs in Los Angeles County, California, to CEP or RS. In 2010, 1246 depressed (Patient Health Questionnaire [PHQ-8] ≥ 10) adults enrolled and were invited for baseline and 6-, 12-, and 36-month surveys. Of 598 3-year completers, 283 participated at 4 years (2016). We examined effects of CEP versus RS, social factors (e.g., family income, food insecurity) on time to and periods in clinical (PHQ-8 < 10) and community-defined (PHQ-8 < 10 or PHQ-2 < 3; mental health composite score [MCS-12] > 40, or mental wellness) remission during the course of 3 years, and at 4 years. Results. We found that CEP versus RS increased 4-year depression remission and, for women, community-defined remission outcomes during the course of 3 years. Social factors and clinical factors predicted remission. Conclusions. At 4 years, CEP was more effective than RS at increasing depression remission. Public Health Implications. Coalitions may improve 4-year depression remission, while addressing social and clinical factors associated with depression may hold potential to enhance remission.

A Clinical Care Monitoring and Data Collection Tool (H3 Tracker) to Assess Uptake and Engagement in Mental Health Care Services in a Community-Based Pediatric Integrated Care Model: Longitudinal Cohort Study.

BACKGROUND: National recommendations for pediatric integrated care models include improved capacity for care coordination and communication across primary care and specialty mental health providers using technology, yet few practical, short-term solutions are available for low-resource, community-based pediatric integrated care clinics. OBJECTIVE: The goal of the paper is to describe the development and features of a Web-based tool designed for program evaluation and clinician monitoring of embedded pediatric mental health care using a community-partnered approach. In addition, a longitudinal study design was used to assess the implementation of the tool in program evaluation, including clinical monitoring and data collection. METHODS: Biweekly meetings of the partnered evaluation team (clinic, academic, and funding partners) were convened over the course of 12 months to specify tool features using a participatory framework, followed by usability testing and further refinement during implementation. RESULTS: A data collection tool was developed to collect clinic population characteristics as well as collect and display patient mental health outcomes and clinical care services from 277 eligible caregiver/child participants. Despite outreach, there was little uptake of the tool by either the behavioral health team or primary care provider. CONCLUSIONS: Development of the H3 Tracker (Healthy Minds, Healthy Children, Healthy Chicago Tracker) in two community-based pediatric clinics with embedded mental health teams serving predominantly minority children is feasible and promising for on-site program evaluation data collection. Future research is needed to understand ways to improve clinic integration and examine whether promotion of primary care/mental health communication drives sustained use. TRIAL REGISTRATION: ClinicalTrials.gov NCT02699814; https://clinicaltrials.gov/ct2/show/NCT02699814 (Archived by WebCite at http://www.webcitation.org/772pV5rWW).

Feasibility of Online Mental Wellness Self-assessment and Feedback for Pediatric and Neonatal Critical Care Nurses.

PURPOSE: The primary goal of this study was to test the feasibility of an educational online self-assessment of burnout, resilience, trauma, depression, anxiety, and common workplace stressors among nurses working in a pediatric intensive care unit or neonatal intensive care unit setting. The secondary, exploratory objectives were to estimate the prevalence of psychiatric symptoms in this sample and to identify those variables that most strongly predict burnout. DESIGN AND METHODS: Data from optional and anonymous online measures were analyzed for 115 nurses (67.9% aged 25-44; 61.7% Caucasian) working in an urban children's hospital pediatric or neonatal ICU. Multiple linear regressions identified demographic variables and workplace stressors that significantly predicted each of three components of burnout. RESULTS: Most respondents found the educational assessment and feedback to be helpful. Choosing nursing as a second career was associated with better resilience. Having worked in ICU settings longer and being older were both linked to lower levels of anxiety. Predictors of burnout varied across the three burnout subscales. CONCLUSIONS: Implementation of an online self-assessment with immediate educational feedback is feasible in critical care settings. The variability of predictors across the three burnout subscales indicates the need for tailored interventions for those at risk. Future research may include follow-up of nurses to examine changes in scores over time and expansion of the tool for other medical personnel. PRACTICE IMPLICATIONS: An educational online self-assessment can be a helpful tool for pediatric critical care nurses experiencing varying degrees of burnout and distress.

Interoceptive Anxiety and Body Representation in Anorexia Nervosa.

Individuals with anorexia nervosa (AN) typically display anxious traits prior to the onset of food avoidance and weight loss that characterize the disorder. Meal associated anxiety is an especially common clinical feature in these patients, and heightened sensitivity to sympathetically mediated interoceptive sensations has also been observed. However, it remains unclear how heightened interoceptive sensitivity relates to experiences of anxiety before and after meals. To investigate this relationship, we experimentally induced anxiety and panic symptoms with isoproterenol, a peripheral sympathetic agonist similar to adrenaline, across several different conditions: during panic provocation, during anticipation of a 1,000 Calorie meal, and after meal consumption. Fifteen AN and 15 age- and sex-matched healthy comparisons received bolus infusions of isoproterenol and saline in a double-blinded, randomized design. Participants rated anxiety symptoms after each infusion, completed panic rating scales, and traced the location of perceived palpitations on a manikin to index interoceptive "body map" representation. The AN group reported significantly elevated anxiety relative to healthy comparisons during infusions before and after the meal, but surprisingly, not during panic provocation. These symptoms were accompanied by geographical differences in patterns of perceived heartbeat sensations across each condition. In particular, the AN group localized heartbeat sensations disproportionately to the chest during meal related saline infusions, when no cardiorespiratory modulation actually occurred. The AN group also showed a trend toward higher panic attack rates during the meal anticipation period. Correcting for anxiety levels reported during saline infusions abolished group differences in anxiety change across all conditions, suggesting a significant contribution of anxious traits in AN. The observation of meal related "visceral illusions" provides further evidence that AN is associated with abnormal interoceptive representation of the heartbeat and suggests that meal consumption, particularly when anticipated, preferentially alters the processing of interoception related signals in AN.

Participatory methods to support team science development for predictive analytics in health.

Predictive analytics in health is a complex, transdisciplinary field requiring collaboration across diverse scientific and stakeholder groups. Pilot implementation of participatory research to foster team science in predictive analytics through a partnered-symposium and funding competition. In total, 85 stakeholders were engaged across diverse translational domains, with a significant increase in perceived importance of early inclusion of patients and communities in research. Participatory research approaches may be an effective model for engaging broad stakeholders in predictive analytics.

The Community and Patient Partnered Research Network (CPPRN): Application of Patient-Centered Outcomes Research to Promote Behavioral Health Equity.

Objective: We describe the rationale, development, and progress on the Community and Patient Partnered Research Network (CPPRN). The CPPRN builds on more than a decade of partnered work and is designed to promote health equity by developing partnered research on behavioral health and social risk factors in Los Angeles and New Orleans. Setting: A community-academic partnership across Los Angeles County and New Orleans. Methods: Review of rationale, history, structure, activities and progress in applying community partnered participatory research (CPPR) to CPPRN. Findings: Patient and community stakeholders participated in all phases of development, including local and national activities. Key developments include partnered planning efforts, progress on aggregating a large, de-identified dataset across county agencies, and development of an information technology-supported screening approach for behavioral and social determinants in health care, social, and community-based settings. Conclusion: The CPPRN represents a promising approach for research data networks, balancing the potential benefit of information technology and data analytic approaches while addressing potential risks and priorities of relevant stakeholders.

Participatory Technology Development to Enhance Community Resilience.

Objective: To assess the feasibility of a novel, partnered technology development process to co-create mobile health applications (apps) addressing community health priorities, using psychoeducation of cognitive behavioral therapy (CBT) principles for enhancing resilience as an example. Design: Stakeholder engagement, workgroups, pilot feasibility study using mixed methods during October 2013 through January 2016 over three phases: 1) defining the vision of the project and increasing technical capacity, 2) co-development and pilot testing of the app, and 3) planning for sustainability. Setting: An academic-community partnership in South Los Angeles, California. Participants: Eight stakeholders; 30 pilot participants from the community. Main Outcome Measures: Qualitative analysis of audio-recordings of the app development process and stakeholder interviews, surveys of stakeholders' perception of the development process, app use data, and feedback from pilot participants. Results: The participatory technology development process resulted in creation and pilot-testing of a resiliency-focused text messaging app. Of the 1,107 messages sent, 23 out of 30 (77%) app users responded to explore interactive content. Stakeholders reported increased perceived competency in creating mobile apps and that the process fostered a culture of co-leadership. There was also sustained engagement in mobile app development by stakeholders beyond the initial project period. Conclusions: This is the first study, to our knowledge, to demonstrate the feasibility of participatory technology development, an approach involving direct participation in the development, tailoring and maintenance of a mobile app by a broad set of stakeholders with high representation from racial/ethnic minorities from an under-resourced community. Participatory technology development is a promising approach for creating sustainable, relevant and engaging health technologies across different technological, clinical and community settings.

The Elicitation of Relaxation and Interoceptive Awareness Using Floatation Therapy in Individuals With High Anxiety Sensitivity.

BACKGROUND: Floatation-REST (Reduced Environmental Stimulation Therapy), an intervention that attenuates exteroceptive sensory input to the nervous system, has recently been found to reduce state anxiety across a diverse clinical sample with high levels of anxiety sensitivity (AS). To further examine this anxiolytic effect, the present study investigated the affective and physiological changes induced by Floatation-REST and assessed whether individuals with high AS experienced any alterations in their awareness for interoceptive sensation while immersed in an environment lacking exteroceptive sensation. METHODS: Using a within-subject crossover design, 31 participants with high AS were randomly assigned to undergo a 90-minute session of Floatation-REST or an exteroceptive comparison condition. Measures of self-reported affect and interoceptive awareness were collected before and after each session, and blood pressure was measured during each session. RESULTS: Relative to the comparison condition, Floatation-REST generated a significant anxiolytic effect characterized by reductions in state anxiety and muscle tension and increases in feelings of relaxation and serenity (p < .001 for all variables). Significant blood pressure reductions were evident throughout the float session and reached the lowest point during the diastole phase (average reduction >12 mm Hg). The float environment also significantly enhanced awareness and attention for cardiorespiratory sensations. CONCLUSIONS: Floatation-REST induced a state of relaxation and heightened interoceptive awareness in a clinical sample with high AS. The paradoxical nature of the anxiolytic effect in this sample is discussed in relation to Wolpe's theory of reciprocal inhibition and the regulation of distress via sustained attention to present moment visceral sensations such as the breath.

Opportunities for Flexible, On-Demand Care Delivery Through Telemedicine.

Efficient response to health care needs when clinical resources are limited is a critical issue in health care delivery. Technologies such as telemedicine hold promise to support adaptive service delivery models to address these issues. The authors explore how a simple, low-tech approach to telemedicine paired with an on-demand staffing model to create a virtual pool of consultants may improve capacity and flexibility for providing inpatient consultation-liaison psychiatric services.