Psychiatry is rapidly adopting digital phenotyping and artificial intelligence/machine learning tools to study mental illness based on tracking participants' locations, online activity, phone and text message usage, heart rate, sleep, physical activity, and more. Existing ethical frameworks for return of individual research results (IRRs) are inadequate to guide researchers for when, if, and how to return this unprecedented number of potentially sensitive results about each participant's real-world behavior. To address this gap, we convened an interdisciplinary expert working group, supported by a National Institute of Mental Health grant. Building on established guidelines and the emerging norm of returning results in participant-centered research, we present a novel framework specific to the ethical, legal, and social implications of returning IRRs in digital phenotyping research. Our framework offers researchers, clinicians, and Institutional Review Boards (IRBs) urgently needed guidance, and the principles developed here in the context of psychiatry will be readily adaptable to other therapeutic areas.

BACKGROUND:Psychiatry has long needed a better and more scalable way to capture the dynamics of behavior and its disturbances, quantitatively across multiple data channels, at high temporal resolution in real time. By combining 24/7 data-on location, movement, email and text communications, and social media-with brain scans, genetics, genomics, neuropsychological batteries, and clinical interviews, researchers will have an unprecedented amount of objective, individual-level data. Analyzing these data with ever-evolving artificial intelligence could one day include bringing interventions to patients where they are in the real world in a convenient, efficient, effective, and timely way. Yet, the road to this innovative future is fraught with ethical dilemmas as well as ethical, legal, and social implications (ELSI). OBJECTIVE:The goal of the Ethics Checklist is to promote careful design and execution of research. It is not meant to mandate particular research designs; indeed, at this early stage and without consensus guidance, there are a range of reasonable choices researchers may make. However, the checklist is meant to make those ethical choices explicit, and to require researchers to give reasons for their decisions related to ELSI issues. The Ethics Checklist is primarily focused on procedural safeguards, such as consulting with experts outside the research group and documenting standard operating procedures for clearly actionable data (eg, expressed suicidality) within written research protocols. METHODS:We explored the ELSI of digital health research in psychiatry, with a particular focus on what we label "deep phenotyping" psychiatric research, which combines the potential for virtually boundless data collection and increasingly sophisticated techniques to analyze those data. We convened an interdisciplinary expert stakeholder workshop in May 2020, and this checklist emerges out of that dialogue. RESULTS:Consistent with recent ELSI analyses, we find that existing ethical guidance and legal regulations are not sufficient for deep phenotyping research in psychiatry. At present, there are regulatory gaps, inconsistencies across research teams in ethics protocols, and a lack of consensus among institutional review boards on when and how deep phenotyping research should proceed. We thus developed a new instrument, an Ethics Checklist for Digital Health Research in Psychiatry ("the Ethics Checklist"). The Ethics Checklist is composed of 20 key questions, subdivided into 6 interrelated domains: (1) informed consent; (2) equity, diversity, and access; (3) privacy and partnerships; (4) regulation and law; (5) return of results; and (6) duty to warn and duty to report. CONCLUSIONS:Deep phenotyping research offers a vision for vastly more effective care for people with, or at risk for, psychiatric disease. The potential perils en route to realizing this vision are significant; however, and researchers must be willing to address the questions in the Ethics Checklist before embarking on each leg of the journey.

The rapidly increasing population living with dementia presents a unique economic and public health challenge. However, primary care physicians, despite their position as first-line providers, often lack the time, support, and training to systematically screen for, diagnose, and treat dementia, as well as provide adequate psychosocial support to unpaid caregivers. Models of collaborative care, which have found success in reducing symptom severity and increasing quality of life for other chronic illnesses, have been studied for feasibility, efficacy, and cost effectiveness in treating individuals with dementia and supporting caregivers. A review of initial data from several models suggests that enrollment in a collaborative care program for dementia is associated with benefits such as reduction in behavioral symptoms of dementia, improved functioning and quality of life, less frequent utilization of acute medical services, and decrease in caregiver burden. These evidence-based models, if implemented widely, stand to facilitate delivery of highly effective dementia care while reducing associated total medical expense. In this narrative review, we examine the key components of collaborative care teams, summarize outcomes of prior studies and discuss barriers and opportunities for wider dissemination of collaborative care models that are partnered with and/or based within primary care settings.

OBJECTIVES:Alzheimer's Disease (AD)-related behavioral symptoms (i.e. agitation and/or pacing) develop in nearly 90% of AD patients. In this N = 1 study, we provide proof-of-concept of detecting changes in movement patterns that may reflect underlying behavioral symptoms using a highly novel radio sensor and identifying environmental triggers.METHODS:The Emerald device is a Wi-Fi-like box without on-body sensors, which emits and processes radio-waves to infer patient movement, spatial location and activity. It was installed for 70 days in the room of patient 'E', exhibiting agitated behaviors.RESULTS:Daily motion episode aggregation revealed motor activity fluctuation throughout the data collection period which was associated with potential socio-environmental triggers. We did not detect any adverse events attributable to the use of the device.CONCLUSION:This N-of-1 study suggests the Emerald device is feasible to use and can potentially yield actionable data regarding behavioral symptom management. No active or potential device risks were encountered.

Introduction Alzheimer's disease (AD) is the most prevalent neurodegenerative disease of aging, affecting approximately 5.4 million individuals in the US, and predicted to increase to 13.8 million by 2050. Occurring in over 90% of AD patients, neuropsychiatric symptoms such as agitation, depression and apathy, contribute to caregiver burden and increase patient morbidity and mortality. With no FDA-approved options available, treatments for severe agitation in people with advanced dementia are limited, with modest evidence for efficacy and substantial safety concerns. Behavioral therapies are recommended as first-line treatments for agitation in AD; however, they require substantial time to take effect and may be less efficacious for the most severely agitated patients. Psychotropic medications, especially antipsychotics, are widely used off-label to treat agitation in AD even with documented limitations in efficacy and safety concerns. Therefore, new treatments for severe agitation in AD refractory to standard interventions are timely and warranted. Randomized controlled trials have demonstrated the safety and efficacy of electroconvulsive therapy (ECT) for the treatment of severe psychiatric disorders of late life, including depression, mania and psychosis. Recently, small open label studies suggest efficacy and safety of ECT for agitation in individuals with AD who are refractory to standard therapies. The present randomized controlled trial builds upon prior work and aims to determine the efficacy and safety of ECT for severe agitation in moderate to severe stage AD, while also examining the durability of the acute treatment effect in an exploratory maintenance naturalistic design. Methods We describe an NIA-funded multi-site, single blind, randomized trial of ECT plus usual care (UC) versus Simulated-ECT (S-ECT) plus UC. We will enroll 200 inpatients with severe agitation and moderate to severe dementia, who have not responded well to prior trials of psychotropic medications. Our primary efficacy outcome measure is the Cohen Mansfield Agitation Inventory (CMAI), and the Neuropsychiatric Inventory – Clinician Version (NPI-C), Alzheimer's Disease Cooperative Study-Clinical Global Impression of Change Scale (ADCS-CGIC), and Pittsburgh Agitation Scale (PAS) will be secondary measures. Safety and tolerability will be assessed with the Severe Impairment Battery – 8 item (SIB-8), the Confusion Assessment Method (CAM), and adverse event monitoring. Results Preliminary open-label data from our team suggests acute ECT treatment is safe and effective in reducing agitation in this population as measured by the CMAI, PAS, CGI, and adverse event monitoring. A multi-site, prospective case series investigated ECT treatment in 23 consecutive inpatients with dementia and severe agitation who did not benefit from standard behavioral interventions and pharmacotherapy. Eighteen of the 23 subjects experienced a significant reduction in agitation from baseline to discharge on the CMAI. In a retrospective chart review study of 16 patients undergoing ECT for agitation related to AD, only two experienced more than transient confusion post-ECT that required treatment, and no other clinically significant adverse events were noted in this group. We hypothesize ECT+UC will be more efficacious in reducing severe agitation in AD subjects than S-ECT+UC, as measured by our primary and secondary efficacy measures, and that there will be no difference in tolerability/safety outcomes for ECT+UC and S-ECT+UC as measured by cognitive decline (SIB-8), development of delirium (CAM), and serious adverse event monitoring. Conclusions This innovative study will fill a gap in the current clinical practice of treating severe agitation in AD using a rigorous methodological approach thus providing evidence for a new therapeutic application (severe agitation in AD) of a well-studied, established, and safe treatment (ECT). Study findings may demonstrate support for a new therapeutic use of ECT for severe agitation in AD. Successful management of neuropsychiatric symptoms reduces long-term care placement, decreases the risk of mortality, and enhances patient and caregiver quality-of-life. Such an approach has the potential to offer enormous relief to the substantial socioeconomic burden of AD-related behavioral disturbances. This research was funded by National Institute of Aging R01 AG061100-01

Obtaining collateral information from a patient is an essential component of providing effective psychiatric and psychotherapeutic care. Research indicates that patients’ social and electronic media contains information relevant to their psychotherapy and clinical care. However, it remains unclear to what degree this content is being actively utilized by clinicians as a part of diagnosis or therapy. Moreover, clinicians’ attitudes around this practice have not been well characterized. This survey aimed to establish the current attitudes and behaviors of outpatient clinicians regarding the incorporation of patients’ social and electronic media into psychotherapy. A Web-based survey was sent to outpatient psychotherapists associated with McLean Hospital in Belmont, Massachusetts. The survey asked clinicians to indicate to what extent and with which patients they reviewed patients’ social and electronic media content as part of their clinical practice, as well as their reasons for or against doing so. Of the total 115 respondents, 71 (61.7%) indicated that they had viewed at least one patient’s social or electronic media as part of psychotherapy, and 65 of those 71 (92%) endorsed being able to provide more effective treatment as a result of this information. The use of either short message service text messages or email was significantly greater than the use of other electronic media platforms (χ21=24.1, n=115, P<.001). Moreover, the analysis of survey responses found patterns of use associated with clinicians’ years of experience and patient demographics, including age and primary diagnosis. The incorporation of patients’ social and electronic media into therapy is currently common practice among clinicians at a large psychiatric teaching hospital. The results of this survey have informed further questions about whether reviewing patient’s media impacts the quality and efficacy of clinical care.

Background: Obtaining collateral information from a patient is an essential component of providing effective psychiatric and psychotherapeutic care. Research indicates that patients' social and electronic media contains information relevant to their psychotherapy and clinical care. However, it remains unclear to what degree this content is being actively utilized by clinicians as a part of diagnosis or therapy. Moreover, clinicians' attitudes around this practice have not been well characterized.Objective: This survey aimed to establish the current attitudes and behaviors of outpatient clinicians regarding the incorporation of patients' social and electronic media into psychotherapy.Methods: A Web-based survey was sent to outpatient psychotherapists associated with McLean Hospital in Belmont, Massachusetts. The survey asked clinicians to indicate to what extent and with which patients they reviewed patients' social and electronic media content as part of their clinical practice, as well as their reasons for or against doing so.Results: Of the total 115 respondents, 71 (61.7%) indicated that they had viewed at least one patient's social or electronic media as part of psychotherapy, and 65 of those 71 (92%) endorsed being able to provide more effective treatment as a result of this information. The use of either short message service text messages or email was significantly greater than the use of other electronic media platforms (chi(2)(1)=24.1, n=115, P<.001). Moreover, the analysis of survey responses found patterns of use associated with clinicians' years of experience and patient demographics, including age and primary diagnosis.Conclusions: The incorporation of patients' social and electronic media into therapy is currently common practice among clinicians at a large psychiatric teaching hospital. The results of this survey have informed further questions about whether reviewing patient's media impacts the quality and efficacy of clinical care.

Behavioral and Psychotic Symptoms in dementia (BPSD) are associated with negative outcomes including increased mortality and morbidity, increased cost of care and caregiver burnout. Over the past decade, technological approaches have been developed to assess and monitor BPSD in real time. However, these have relied on complex arrays of sensors and generate complex data that may not lend themselves to efficient clinical use. In this study we utilized a novel passive sensing approach supported by AI to demonstrate how highly specific behavioral phenomena can be detected in real time with limited need for in-person supervision and monitoring. Emerald is a device developed at MIT for in-home, non-intrusive patient monitoring. The device transmits low-power radio signals (100x lower power than WiFi) and monitors the reflection of these signals from people/their environment to map behavioral information. Signal data are uploaded to the cloud where customized machine learning algorithms process the data to extract gait speed, sleep patterns, spatial location, respiration Subject: We installed the device in the rooms of 4 adults with Dementia in an assisted living facility outside Boston. We measured the subjects’ behavior continuously for 3 months. Sensor data findings were compared to staff observations around specific behavior phenomena. Our goal was to demonstrate Emerald's ability to accurately capture a range of BPSD. Over the course of the study, we identified four behavioral phenomena using the sensor, that were verified by staff and validated by standardized behavioral measures. These include apathy, hypersomnia, anxiety and psychomotor agitation. This aimed at demonstrating the feasibility of an AI-backed passive sensor-based device to accurately phenotype a range of behavioral phenomena. Our initial findings demonstrate that this technology can identify movement-based behavior symptoms accurately. These findings bear validation in larger samples against standardized clinical rating scales.

Introduction Behavioral symptoms of Alzheimer's disease (e.g. delusions, wandering, aggression, sleep disturbance) lead to increased emergency room visits, caregiver burden, and transfers to memory care facilities. Sensor technologies may hold the potential to facilitate early detection and pre-emptive intervention for these symptoms by enabling continuous passive monitoring in a way that in-person monitoring may not be able to. We present preliminary data for such an approach using a device called the Emerald, developed at MIT, which emits low-powered radio signals and can identify and track parameters related to human behavior (sleep, motion, spatial motion, and respiratory rate) based on how these waves reflect off the human body. Artificial Intelligence (AI) algorithms elicit behavioral markers from sensor data. The device does not require any contact or direct interaction by the person being monitored, thus representing true passive sensing. Methods The Emerald device was installed in the rooms of two dementia patients (N=2) with behavioral symptoms residing in an assisted living facility (ALF). Motion data was gathered continuously for a period of three months and was mapped on to spatial location and time frame. Data processing and analysis occurred simultaneously during the collection period. Additionally, study staff administered weekly standardized assessments to both the participant (MMSE) and ALF staff (NPI-NH, CMAI, PAS) to augment data collected from the Emerald. Device data was compiled and made available to the study clinician for clinical analysis and identification of emergent behavioral complications. Results In both participants, device data were used to identify specific behavioral patterns. The device detected variations in behavior by time of day, escalations in pacing, and moments of restlessness throughout the night for both participants. For one participant, clinical interpretation of device data led to the proposition that the participant was experiencing Periodic Limb Movement Disorder, which was unbeknownst to the participant or clinician prior to study participation. The device was able to identify periodic spasms, which occurred when the person was asleep, and localize these to the patient's legs. The second participant showed increase pacing, wandering, and motor agitation before being hospitalized for heightened anxiety and aggression. Device data indicates the period prior to hospitalization featured increased movement episodes relative to this participant's baseline. Conclusions We propose that behavioral phenotyping using an AI-backed passive sensing approach is feasible and safe, and that this approach can help digitally phenotype behavior symptoms in dementia. While the device merits validation against the current standard of behavior measurement in dementia, its advantages include low cost and ongoing engagement, and continuous monitoring while giving patients the option of stopping monitoring at their discretion. Further studies evaluating sensitivity and reliability are warranted to validate the clinical utility of this device. This research was funded by This project is supported by an Innovations grant from the Massachusetts Institute of Technology.

Purpose of Review Recent advances in technology have changed the landscape of treatment for adults with mental illness. This review highlights technological innovations that may improve care for older adults with mental illness and neurocognitive disorders through the measurement and assessment of physical motion. These technologies include wearable sensors (such as smart watches and Fitbits), passive motion sensors, and smart home models that incorporate both active and passive motion technologies. Recent Findings Clinicians have evaluated motion measurement technologies in older adults with depression, dementia, anxiety, and schizophrenia. Results from studies in dementia populations suggest that motion measurement technologies can assist clinicians in diagnosing dementia earlier through the evaluation of gait, balance, and postural kinematics. Motion detection technologies can also be used to identify mood episodes at an earlier stage by detecting subtle behavioral changes. Summary Clinicians may use the objective data provided by technologies such as accelerometers to identify illnesses earlier, which may inform treatment decisions. The data may be used as a suitable surrogate marker for detecting depression in older adults, predicting the likelihood of falls, or quantifying physical activity in older adults with chronic mental illnesses or anxiety. Motion-based technologies also have the potential to detect physical activity for older adults residing in nursing homes. Wearable technologies are generally well tolerated in older adults, although the use of new technology and electronic health data could involve privacy and security concerns among this vulnerable population.

AbstractStreptococcus mutans, one of ∼600 bacterial species in the human oral cavity, is among the most acidogenic constituents of the plaque biofilm. Considered to be the primary causative agent of dental caries,S. mutansharbors a 25kDa SloR metalloregulatory protein which controls metal ion transport across the bacterial cell membrane to maintain essential metal ion homeostasis. The expression of SloR derives, in part, from transcriptional readthrough of thesloABCoperon which encodes a Mn2+/Fe2+ABC transport system. Herein, we describe the details of thesloABCpromoter that drives this transcription, as well as a novel independent promoter in an intergenic region (IGR) that contributes to downstreamsloRexpression. RT-PCR studies supportsloRtranscription that is independent ofsloABCexpression, and the results of 5′ RACE revealed asloRtranscription start site in the IGR from which the −10 and −35 promoter regions were predicted. The results of gel mobility shift assays support direct SloR binding to the IGR, albeit with lower affinity than SloR binding to thesloABCRpromoter. Function of thesloRpromoter was validated in qRT-PCR experiments. Interestingly,sloRexpression was not significantly impacted when grown in the presence of high manganese, whereas expression of thesloABCoperon was repressed under these conditions. The results ofin vitrotranscription studies support SloR-mediated transcriptional-activation ofsloRand -repression ofsloABC.Taken together, these findings implicate SloR as a bifunctional regulator that repressessloABCpromoter activity and encouragessloRtranscription from an independent promoter.ImportanceTooth decay is a ubiquitous infectious disease that is especially pervasive in underserved communities worldwide.S. mutans-induced carious lesions cause functional, physical, and/or aesthetic impairment in the vast majority of adults, and in 60-90% of schoolchildren in industrialized countries. Billions of dollars are spent annually on caries treatment, and productivity losses due to absenteeism from the workplace are significant. Research aimed at alleviatingS. mutans-induced tooth decay is important because it can address the socioeconomic disparity that is associated with dental cavities and improve overall general health which is inextricably linked to oral health. Research focused on theS. mutansSloR metalloregulatory protein can guide the development of novel therapeutics and so alleviate the burden of dental cavities.

ABSTRACT Streptococcus mutans, one of ∼600 bacterial species in the human oral cavity, is among the most acidogenic constituents of the plaque biofilm. Considered to be the primary causative agent of dental caries, S. mutans harbors a 25-kDa SloR metalloregulatory protein which controls metal ion transport across the bacterial cell membrane to maintain essential metal ion homeostasis. The expression of SloR derives in part from transcriptional readthrough of the sloABC operon, which encodes a Mn2+/Fe2+ ABC transport system. Here we describe the details of the sloABC promoter that drives this transcription as well as those for a novel independent promoter in an intergenic region (IGR) that contributes to downstream sloR expression. Reverse transcriptase PCR (RT-PCR) studies support the occurrence of sloR transcription that is independent of sloABC expression, and the results of 5′ rapid amplification of cDNA ends (5′ RACE) revealed a sloR transcription start site in the IGR, from which the −10 and −35 promoter regions were predicted. The results of gel mobility shift assays support direct SloR binding to the IGR, albeit with a lower affinity than that for SloR binding to the sloABCR promoter. The function of the sloR promoter was validated by semiquantitative real-time PCR (qRT-PCR) experiments. Interestingly, sloR expression was not significantly affected when bacteria were grown in the presence of a high manganese concentration, whereas expression of the sloABC operon was repressed under these conditions. The results of in vitro transcription studies support the occurrence of SloR-mediated transcriptional activation of sloR and repression of sloABC. Taken together, these findings implicate SloR as a bifunctional regulator that represses sloABC promoter activity and encourages sloR transcription from an independent promoter. IMPORTANCE Tooth decay is a ubiquitous infectious disease that is especially pervasive in underserved communities worldwide. S. mutans-induced carious lesions cause functional, physical, and/or esthetic impairment in the vast majority of adults and in 60 to 90% of schoolchildren in industrialized countries. Billions of dollars are spent annually on caries treatment, and productivity losses due to absenteeism from the workplace are significant. Research aimed at alleviating S. mutans-induced tooth decay is important because it can address the socioeconomic disparity that is associated with dental cavities and improve overall general health, which is inextricably linked to oral health. Research focused on the S. mutans SloR metalloregulatory protein can guide the development of novel therapeutics and thus alleviate the burden of dental cavities.

The prevalence of mood disorders in the rapidly-growing older adult population merits attention due to the likelihood of increased medical comorbidities, risk of hospitalization or institutionalization, and strains placed on caregivers and healthcare providers. Magnetic resonance spectroscopy (MRS) quantifies biochemical compounds in vivo, and has been used specifically for analyses of neural metabolism and bioenergetics in older adults with mood disorders, usually via proton or phosphorous spectroscopy. While yet to be clinically implemented, data gathered from research subjects may help indicate potential biomarkers of disease state or trait or putative drug targets. Three prevailing hypotheses for these mood disorders are used as a framework for the present review, and the current biochemical findings within each are discussed with respect to particular metabolites and brain regions. This review covers studies of MRS in geriatric mood disorders and reveals persisting gaps in research knowledge, especially with regard to older age bipolar disorder. Further MRS work, using higher field strengths and larger sample sizes, is warranted in order to better understand the neurobiology of these prevalent late-life disorders.

Abstract The prevalence of mood disorders in the rapidly-growing older adult population merits attention due to the likelihood of increased medical comorbidities, risk of hospitalization or institutionalization, and strains placed on caregivers and healthcare providers. Magnetic resonance spectroscopy (MRS) quantifies biochemical compounds in vivo, and has been used specifically for analyses of neural metabolism and bioenergetics in older adults with mood disorders, usually via proton or phosphorous spectroscopy. While yet to be clinically implemented, data gathered from research subjects may help indicate potential biomarkers of disease state or trait or putative drug targets. Three prevailing hypotheses for these mood disorders are used as a framework for the present review, and the current biochemical findings within each are discussed with respect to particular metabolites and brain regions. This review covers studies of MRS in geriatric mood disorders and reveals persisting gaps in research knowledge, especially with regard to older age bipolar disorder. Further MRS work, using higher field strengths and larger sample sizes, is warranted in order to better understand the neurobiology of these prevalent late-life disorders.

Cell death and release of proinflammatory mediators contribute to mortality during sepsis. Specifically, caspase-11-dependent cell death contributes to pathology and decreases in survival time in sepsis models. Priming of the host cell, through TLR4 and interferon receptors, induces caspase-11 expression, and cytosolic LPS directly stimulates caspase-11 activation, promoting the release of proinflammatory cytokines through pyroptosis and caspase-1 activation. Using a CRI SPR-Cas9-mediated genome-wide screen, we identified novel mediators of caspase-11-dependent cell death. We found a complement-related peptidase, carboxypeptidase B1 (Cpb1), to be required for caspase-11 gene expression and subsequent caspase-11-dependent cell death. Cpb1 modifies a cleavage product of C3, which binds to and activates C3aR, and then modulates innate immune signaling. We find the Cpb1-C3-C3aR pathway induces caspase-11 expression through amplification of MAPK activity down-stream of TLR4 and Ifnar activation, and mediates severity of LPS-induced sepsis (endotoxemia) and disease outcome in mice. We show C3aR is required for up-regulation of caspase-11 orthologues, caspase-4 and -5, in primary human macrophages during inflammation and that c3aR1 and caspase-5 transcripts are highly expressed in patients with severe sepsis; thus, suggesting that these pathways are important in human sepsis. Our results highlight a novel role for complement and the Cpb1-C3-C3aR pathway in proinflammatory signaling, caspase-11 cell death, and sepsis severity.