TY - JOUR AU - Kang, Minhee AU - Park, Eunkyoung AU - Cho, Baek Hwan AU - Lee, Kyu-sung IS - Suppl 2 KW - 2016m3a9b6919189 KW - and the bio KW - by the korea health KW - d project through the KW - fund KW - funded by the ministry KW - grant support KW - healthcare KW - hi14c3228 KW - institute KW - khidi KW - korea health industry development KW - medical technology development program KW - national research foundation KW - nrf KW - of health KW - of science KW - of the KW - self-monitoring KW - technology r KW - this work was supported KW - wearable device KW - welfare PY - 2018 SN - 0000000241069 SP - 76 EP - 82 TI - of Things-Enabled Smart Devices VL - 22 ER - TY - JOUR AB - © 2016, Fundacao Oswaldo Cruz. All rights reserved. Hospital readmissions are common and expensive, and there is little information on the problem in Colombia. The objective was to determine the frequency of 30-day all-cause hospital readmissions and associated factors. This was a retrospective analytical cohort study of 64,969 hospitalizations from January 2008 to January 2009 in 47 Colombian cities. 6,573 hospital readmissions, prevalence: 10.1% (men 10.9%, women 9.5%), 44.7% > 65 years of age. Hospital readmissions was associated with higher mortality (5.8% vs. 1.8%). There was an increase in the Hospital readmissions rate in patients with diseases of the circulatory system. Hospital readmissions was more likely in hematological diseases and neoplasms. Mean length of stay during the first readmission was 7 days in patients that were readmitted and 4.5 in those without readmission. Greater total cost of hospital readmissions (USA 21,998,275): 15.8% of the total cost of hospitalizations. Higher prevalence rates in referred patients (18.8%) and patients from the outpatient clinic (13.7%). Hospital readmissions is common and is associated with longer length of hospital stay and higher mortality and cost. Increased risk of hospital readmissions in men > 65 years, patients referred from other institutions, and in hematological diseases and neoplasms. AU - Caballero, Andrés AU - Pinilla, Milciades Ibañez AU - Mendoza, Isabel Cristina Suárez AU - Peña, Juan Ramón Acevedo DO - 10.1590/0102-311X00146014 IS - 7 KW - Health care costs KW - Hospitalization KW - Patient readmission PY - 2016 SP - 1 EP - 12 TI - Hospital readmission rate and associated factors among health services enrollees in Colombia T2 - Cadernos de Saude Publica VL - 32 ER - TY - JOUR AB - La “Conferencia Regional para la Reforma de los Servicios de Salud Mental: 15 años después de Caracas”, fue celebrada en Brasilia, del 7 al 9 de noviembre del 2005, bajo el patrocinio conjunto de la Organización Panamericana de la Salud (OPS), la Organización Mundial de la Salud (OMS) y el Ministerio de Salud de la República Federativa de Brasil. El encuentro contó con una amplia participación; estuvieron presentes funcionarios gubernamentales del sector salud, profesionales de las ciencias de la conducta, representantes de organizaciones de la sociedad civil y portavoces de usuarios y familiares de la Región de las Américas, así como expertos de diversos organismos. AU - Organización Panamericana De La Salud PY - 2005 SN - 927532607 X SP - 27 EP - 34 TI - La reforma de los servicios de salud mental: 15 años después de la delcaración de Caracas T2 - La reforma de los servicios de salud mental: 15 años después de la delcaración de Caracas UR - http://www1.paho.org/hq/dmdocuments/2009/Reforma de las servicos de sald mental.pdf%0Ahttp://new.paho.org/hq/dmdocuments/2009/54-VisionSaludInterculturalPI.pdf VL - 1 ER - TY - JOUR AB - Background: A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. Objective: Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. Methods: We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. Results: We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. Conclusions: Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health. AU - Torous, John AU - Kiang, Mathew V AU - Lorme, Jeanette AU - Onnela, Jukka-Pekka DO - 10.2196/mental.5165 IS - 2 KW - 2 KW - 2016 KW - e16 KW - evaluation KW - http KW - informatics KW - jmir KW - mental KW - mental health KW - org KW - schizophrenia KW - smartphone PY - 2016 SP - e16 EP - e16 TI - New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research T2 - JMIR Mental Health VL - 3 ER - TY - JOUR AB - People with severe mental illness have multiple and complex needs that often are not addressed. The purpose of this study was to analyse needs and support perceived and the relationship with hospital readmission. We assessed 100 patients with severe mental illness at discharge from an acute inpatient unit in terms of needs (Camberwell Assessment of Needs), clinical status (The Brief Psychiatric Rating Scale), and social functioning (Personal and Social Performance); we also followed up these patients for 1 year. The group of patients who were readmitted had more total needs than did the non-readmitted, in addition to more unmet needs, although the differences were not significant. The highest risk factor for rehospitalisation was the number of previous admissions. In addition, the help of informal carers in alleviating psychological distress was associated with the risk of readmission. The main conclusion concerns the role of the psychological support provided by informal networks in preventing readmission. AU - Guzman-Parra, Jose AU - Moreno-Küstner, Berta AU - Rivas, Fabio AU - Alba-Vallejo, Mercedes AU - Hernandez-Pedrosa, Javier AU - Mayoral-Cleries, Fermin DO - 10.1007/s10597-017-0095-x IS - 2 KW - Needs KW - Perceived Support KW - Readmissions KW - Severe Mental illness PB - Springer US PY - 2018 SN - 0123456789 SP - 189 EP - 196 TI - Needs, Perceived Support, and Hospital Readmissions in Patients with Severe Mental Illness T2 - Community Mental Health Journal VL - 54 ER - TY - JOUR AB - Objective: Mental or substance use disorders (M/SUD) are major contributors of disease burden with high risk for hospital readmissions. We sought to develop and evaluate a readmission model using a machine learning (ML) approach. Methods: We analyzed patients with continuous enrollment for three years and at least one episode of M/SUD as the primary reason for hospital admission. The outcome was readmission within 30-days from discharge. Model performance was evaluated using the Area under the Receiver Operating Characteristic (AUROC). We compared the AUROCs of an extreme gradient boosted tree (XGBoost) model to generalized linear model with elastic net regularization (GLMNet). Results: We analyzed 65,426 unique patients and 97,688 admissions. Patients with mental disorders accounted for 66 % (13.2 % readmission rate) and substance use disorders, 34 % (22.3 % readmission rate). Among all those who had readmissions, 70.7 %, 17.0 %, and 12.4 % had 1, 2, or 3+ readmissions, respectively. Previous hospitalizations, hospital utilization, discharge disposition, diagnosis category, and comorbidity were among the highest important features in the XGBoost model. The XGBoost model AUROC was 0.737 (95 % CI: 0.732 to 0.742) versus the GLMNet 0.697 (95 % CI: 0.690 to 0.703). The AUROC of the final XGBoost model on the testing set was 0.738 (95 % CI: 0.730 to 0.748), higher than published readmission models for mental health patients. Conclusions: The XGBoost model has a better performance than GLMNet and previously published models in predicting readmissions in mental health patients. Our model may be further tested to aid targeted demographic initiatives to reduce M/SUDs readmissions and benchmarking. AU - Morel, Didier AU - Yu, Kalvin C. AU - Liu-Ferrara, Ann AU - Caceres-Suriel, Ambiorix J. AU - Kurtz, Stephan G. AU - Tabak, Ying P. DO - 10.1016/j.ijmedinf.2020.104136 IS - February KW - Machine learning KW - Mental disorder KW - Mental health KW - Readmission KW - Substance use disorders PB - Elsevier PY - 2020 SP - 104136 EP - 104136 TI - Predicting hospital readmission in patients with mental or substance use disorders: A machine learning approach T2 - International Journal of Medical Informatics UR - https://doi.org/10.1016/j.ijmedinf.2020.104136 VL - 139 ER - TY - JOUR AU - Al, L A Adherencia AU - Con, Pacientes PY - 2019 TI - THE ADHERENCE TO TREATMENT IN PATIENTS WITH PSYCHOTIC VL - 85 ER - TY - JOUR AU - Lee Ventola, C. IS - 5 PY - 2014 SP - 356 EP - 364 TI - Mobile devices and apps for health care professionals: Uses and benefits T2 - P and T VL - 39 ER - TY - JOUR AB - In a quasi-experimental study, decision support software was installed in three hospitals to study the ability to scale (spread) its use from one hospital on paper to three hospitals as software, and to examine the effect on 30- and 60-day readmissions. The Discharge Decision Support System (D2S2) software analyzes data collected by nurses on admission with a proprietary risk assessment tool, identifies patients in need of post-acute care, and alerts discharge planners. On six intervention units, with a concurrent comparison group of 76 units, we examined the implementation experience and compared readmission outcomes before and after implementation. The software implementation finished one month ahead of schedule, and the software performed reliably. High-risk patients admitted in the experimental phase after implementation of D2S2 decision support had significantly fewer 30-day readmissions (a decrease from 22.2% to 9.4%). When high- and low-risk patients were analyzed together, D2S2 achieved a 33% relative reduction in 30-day readmissions (13.1 to 8.8%) and sustained a 37% relative reduction at 60 days. The software, available commercially through RightCare Solutions, was adopted by the health system and remains in use after 22 months. The D2S2 risk assessment tool can be installed easily in existing EHR systems. Future research will focus on how the tool influences discharge decision-making and how its accuracy can be improved in specific settings. AU - Bowles, Kathryn H. AU - Chittams, Jesse AU - Heil, Eric AU - Topaz, Maxim AU - Rickard, Kathy AU - Bhasker, Mrinal AU - Tanzer, Matt AU - Behta, Maryam AU - Hanlon, Alexandra L. DO - 10.1002/nur.21643 IS - 2 KW - Case management KW - D2S2 KW - Decision support KW - Discharge planning KW - Nursing informatics KW - Quality improvement KW - Readmission KW - Risk stratification PY - 2015 SP - 102 EP - 114 TI - Successful electronic implementation of discharge referral decision support has a positive impact on 30- and 60-day readmissions T2 - Research in Nursing and Health VL - 38 ER - TY - JOUR AB - This systematic review assesses the feasibility and efficacy of social networking or enterprise social networking for promoting healthy lifestyles or for occupational health and safety (OHS) prevention. Literature searches were conducted in several indexed databases in order to retrieve studies whose main objective was the promotion of healthy lifestyles or the prevention of occupational injuries by means of social media or enterprise social networking alone or in combination with others promotional or preventive interventions. Ten studies were included. Results suggest that social media may be considered a possible means of communication for the promotion of healthy lifestyle habits in organizations, however further study into this technology has been recommended by several authors to judge the incremental impacts of social media on the promotion of healthy lifestyles. Similar conclusions were drawn from studies that included the use of a social media platform for OHS prevention. Based on current evidence, an organization's use of social media to promote a healthy lifestyle or OHS among its employees can constitute an innovative and promising means of intervention. It is important to mention that due to the scarcity and poor methodological quality of existing evidence, it is difficult at this time to draw firm conclusions regarding its effectiveness and relevance. AU - Laroche, Elena AU - L'Espérance, Sylvain AU - Mosconi, Elaine DO - 10.1016/j.ssci.2020.104931 IS - July KW - Enterprise social networking KW - Healthy lifestyles KW - Occupational health and safety KW - Social media KW - Social networking KW - Workplace PB - Elsevier PY - 2020 SP - 104931 EP - 104931 TI - Use of social media platforms for promoting healthy employee lifestyles and occupational health and safety prevention: A systematic review T2 - Safety Science UR - https://doi.org/10.1016/j.ssci.2020.104931 VL - 131 ER - TY - JOUR AB - The healthcare industry is changing at a fast rate. Recently, big data real time computing has been studied to enhance the quality of healthcare services and reduce costs making decisions in real-time. Artificial intelligence is used to track the big data. AI in healthcare sector could make treatment plans better, and also provide physicians information they need to make a good decision. This paper proposes a generic architecture for big data healthcare analytic by using open sources, including Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, Elastic search and NoSQL Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing. AU - Kaur, Jagreet AU - Mann, Kulwinder Singh DO - 10.1007/978-981-13-0755-3_11 KW - Big data KW - Elastic search KW - Health care analytics KW - Kafka KW - NiFi KW - NoSQL cassandra KW - Real-time KW - Spark KW - Stream computing PY - 2018 SN - 9789811307546 SP - 138 EP - 149 TI - AI based healthcare platform for real time, predictive and prescriptive analytics T2 - Communications in Computer and Information Science VL - 805 ER - TY - JOUR AU - Roman, David H AU - Conlee, Kyle D PY - 2015 TI - The Digital Revolution comes to US Healthcare: Investment report T2 - Internet of Things VL - 5 ER - TY - JOUR AB - Background: Web-based self-directed mental health applications are rapidly emerging to address health service gaps and unmet needs for information and support. Objective: The aim of this study was to determine if a multicomponent, moderated Web-based mental health application could benefit individuals with mental health symptoms severe enough to warrant specialized mental health care. Methods: A multicenter, pragmatic randomized controlled trial was conducted across several outpatient mental health programs affiliated with 3 hospital programs in Ontario, Canada. Individuals referred to or receiving treatment, aged 16 years or older, with access to the internet and an email address, and having the ability to navigate a Web-based mental health application were eligible. A total of 812 participants were randomized 2:1 to receive immediate (immediate treatment group, ITG) or delayed (delayed treatment group, DTG) access for 3 months to the Big White Wall (BWW), a multicomponent Web-based mental health intervention based in the United Kingdom and New Zealand. The primary outcome was the total score on the Recovery Assessment Scale, revised (RAS-r) which measures mental health recovery. Secondary outcomes were total scores on the Patient Health Questionnaire-9 item (PHQ-9), the Generalized Anxiety Disorder Questionnaire-7 item (GAD-7), the EuroQOL 5-dimension quality of life questionnaire (EQ-5D-5L), and the Community Integration Questionnaire. An exploratory analysis examined the association between actual BWW use (categorized into quartiles) and outcomes among study completers. Results: Intervention participants achieved small, statistically significant increases in adjusted RAS-r score (4.97 points, 95% CI 2.90 to 7.05), and decreases in PHQ-9 score (−1.83 points, 95% CI −2.85 to −0.82) and GAD-7 score (−1.55 points, 95% CI −2.42 to −0.70). Follow-up was achieved for 55% (446/812) at 3 months, 48% (260/542) of ITG participants and 69% (186/270) of DTG participants. Only 58% (312/542) of ITG participants logged on more than once. Some higher BWW user groups had significantly greater improvements in PHQ-9 and GAD-7 relative to the lowest use group. Conclusions: The Web-based application may be beneficial; however, many participants did not engage in an ongoing way. This has implications for patient selection and engagement as well as delivery and funding structures for similar Web-based interventions. AU - Hensel, Jennifer M. AU - Shaw, James AU - Ivers, Noah M. AU - Desveaux, Laura AU - Vigod, Simone N. AU - Cohen, Ashley AU - Onabajo, Nike AU - Agarwal, Payal AU - Mukerji, Geetha AU - Yang, Rebecca AU - Nguyen, Megan AU - Bouck, Zachary AU - Wong, Ivy AU - Jeffs, Lianne AU - Jamieson, Trevor AU - Sacha Bhatia, R. DO - 10.2196/10838 IS - 6 KW - Anxiety KW - Depression KW - Internet KW - Mental health PY - 2019 SP - 1 EP - 12 TI - A web-based mental health platform for individuals seeking specialized mental health care services: Multicenter pragmatic randomized controlled trial T2 - Journal of Medical Internet Research VL - 21 ER - TY - JOUR AB - Mental disorders that commonly emerge during adolescence and young adulthood are associated with substantial immediate burden and risks, as well as potentially imparting lifetime morbidity and premature mortality. While the development of health services that are youth focused and prioritize early intervention has been a critical step forward, an ongoing challenge is the heterogeneous nature of symptom profiles and illness trajectories. Consequently, it is often difficult to provide quality mental health care, at scale, that addresses the broad range of health, social, and functional needs of young people. Here, we describe a new digital platform designed to deliver personalized and measurement-based care. It provides health services and clinicians with the tools to directly address the multidimensional needs of young people. The term “personalized” describes the notion that the assessment of, and the sequence of interventions for, mental disorders are tailored to the young person—and their changing needs over time, while “measurement-based” describes the use of systematic and continuing assessment of a young person’s outcomes over the entire course of clinical care. Together, these concepts support a framework for care that transcends a narrow focus on symptom reduction or risk reduction. Instead, it prioritizes a broader focus on enhancing social, health, and physical outcomes for young people and a commitment to tracking these outcomes throughout this key developmental period. Now, with twenty-first century technologies, it is possible to provide health services with the tools needed to deliver quality mental health care. AU - Iorfino, Frank AU - Cross, Shane P. AU - Davenport, Tracey AU - Carpenter, Joanne S. AU - Scott, Elizabeth AU - Shiran, Sagit AU - Hickie, Ian B. DO - 10.3389/fpsyt.2019.00595 IS - August KW - ehealth KW - mental disorders KW - mental health care KW - routine outcome monitoring KW - technology KW - transdiagnostic KW - youth PY - 2019 SP - 1 EP - 9 TI - A Digital Platform Designed for Youth Mental Health Services to Deliver Personalized and Measurement-Based Care T2 - Frontiers in Psychiatry VL - 10 ER - TY - GEN AU - Prieto Oreja, José AU - Guisado Macías, Juan Antonio DO - 10.5538/2385-703x.2017.7.39 IS - 7 KW - hospital KW - psiquiatría KW - reingreso PY - 2017 SP - 39 EP - 49 TI - Estudio descriptivo del reingreso de pacientes con enfermedad mental en la unidad de hospitalización breve del hospital de Mérida (Badajoz) del Servicio Extremeño de Salud T2 - Revista de Enfermería y Salud Mental ER - TY - JOUR AB - Hospital readmission rates are increasingly used as a performance indicator. Whether they are a valid, reliable, and actionable measure for behavioral health is unknown. Using the MarketScan Multistate Medicaid Claims Database, this study examined hospital- and patient-level predictors of behavioral health readmission rates. Among hospitals with at least 25 annual admissions, the median behavioral health readmission rate was 11% (10th percentile, 3%; 90th percentile, 18%). Increased follow-up at community mental health centers was associated with lower probabilities of readmission, although follow-up with other types of providers was not significantly associated with hospital readmissions. Hospital average length of stay was positively associated with lower readmission rates; however, the effect size was small. Patients with a prior inpatient stay, a substance use disorder, psychotic illness, and medical comorbidities were more likely to be readmitted. Additional research is needed to further understand how the provision of inpatient services and post-discharge follow-up influence readmissions. © 2013 Springer Science+Business Media, LLC. AU - Mark, Tami AU - Tomic, Karen Smoyer AU - Kowlessar, Niranjana AU - Chu, Bong Chul AU - Vandivort-Warren, Rita AU - Smith, Shelagh DO - 10.1007/s11414-013-9323-5 IS - 2 PY - 2013 SN - 1301214221 SP - 207 EP - 221 TI - Hospital readmission among medicaid patients with an index hospitalization for mental and/or substance use disorder T2 - Journal of Behavioral Health Services and Research VL - 40 ER - TY - JOUR AU - De, Análisis PY - 2020 SP - 6679 EP - 6679 TI - Análisis de costo del tratamiento ER - TY - JOUR AB - Background: Heart failure (HF) is a condition that affects approximately 6.2 million people in the United States and has a 5-year mortality rate of approximately 42%. With the prevalence expected to exceed 8 million cases by 2030, projections estimate that total annual HF costs will increase to nearly US $70 billion. Recently, the advent of remote monitoring technology has significantly broadened the scope of the physician’s reach in chronic disease management. Objective: The goal of our program, named the Heart Health Program, was to examine the feasibility of using digital health monitoring in real-world home settings, ascertain patient adoption, and evaluate impact on 30-day readmission rate. Methods: A digital medicine software platform developed at Mount Sinai Health System, called RxUniverse, was used to prescribe a digital care pathway including the HealthPROMISE digital therapeutic and iHealth mobile apps to patients’ personal smartphones. Vital sign data, including blood pressure (BP) and weight, were collected through an ambulatory remote monitoring system that comprised a mobile app and complementary consumer-grade Bluetooth-connected smart devices (BP cuff and digital scale) that send data to the provider care teams. Care teams were alerted via a Web-based dashboard of abnormal patient BP and weight change readings, and further action was taken at the clinicians’ discretion. We used statistical analyses to determine risk factors associated with 30-day all-cause readmission. Results: Overall, the Heart Health Program included 58 patients admitted to the Mount Sinai Hospital for HF. The 30-day hospital readmission rate was 10% (6/58), compared with the national readmission rates of approximately 25% and the Mount Sinai Hospital’s average of approximately 23%. Single marital status (P=.06) and history of percutaneous coronary intervention (P=.08) were associated with readmission. Readmitted patients were also less likely to have been previously prescribed angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (P=.02). Notably, readmitted patients utilized the BP and weight monitors less than nonreadmitted patients, and patients aged younger than 70 years used the monitors more frequently on average than those aged over 70 years, though these trends did not reach statistical significance. The percentage of the 58 patients using the monitors at least once dropped from 83% (42/58) in the first week after discharge to 46% (23/58) in the fourth week. Conclusions: Given the increasing burden of HF, there is a need for an effective and sustainable remote monitoring system for HF patients following hospital discharge. We identified clinical and social factors as well as remote monitoring usage trends that identify targetable patient populations that could benefit most from integration of daily remote monitoring. In addition, we demonstrated that interventions driven by real-time vital sign data may greatly aid in reducing hospital readmissions and costs while improving patient outcomes. AU - Park, Christopher AU - Otobo, Emamuzo AU - Ullman, Jennifer AU - Rogers, Jason AU - Fasihuddin, Farah AU - Garg, Shashank AU - Kakkar, Sarthak AU - Goldstein, Marni AU - Chandrasekhar, Sai Vishudhi AU - Pinney, Sean AU - Atreja, Ashish DO - 10.2196/13353 IS - 11 KW - Blood pressure KW - Blood pressure monitors KW - Body weight KW - Cell phone KW - Heart failure KW - MHealth KW - Mobile apps KW - Mobile phone KW - Patient care management KW - Patient readmission KW - Remote consultation PY - 2019 SP - 1 EP - 10 TI - Impact on readmission reduction among heart failure patients using digital health monitoring: Feasibility and adoptability study T2 - Journal of Medical Internet Research VL - 21 ER - TY - JOUR AU - Madi, Nawaf AU - Zhao, Helen AU - Li, Jerry Fang DO - 10.12927/hcq.2007.18818 IS - 2 PY - 2007 SP - 30 EP - 32 TI - Hospital readmissions for patients with mental illness in Canada. T2 - Healthcare quarterly (Toronto, Ont.) VL - 10 ER - TY - JOUR AB - Background: The impact of a new class of automated digital patient engagement (DPE) platforms on potentially avoidable costs, hospital admissions, and complications after discharge following hip and knee arthroplasties has not been established. Methods: We conducted a multicenter observational cohort study comparing claims data for potentially avoidable costs, hospital admissions, and complications for 90 days after discharge following hip and knee arthroplasties at 10 practice sites in CA and NV. One hundred eighty-six patients, enrolled between 2014 and 2016 on an automated DPE platform receiving guidance and remote monitoring perioperatively, were compared with 372 patients who underwent the same procedures from the same physicians within 3 years immediately preceding platform implementation. The primary end point was the proportion of patients with $0.00 in 90-day target costs because of potentially avoidable utilization within the platform's influence. Secondary end points included rates of potentially avoidable 90-day hospital admissions and composite complications. Results: Ninety-three percent and 84.7% of the study and baseline cohorts, respectively, had $0.00 in target costs (P =.004), with a mean savings of $656.52/patient (P =.006). The baseline and study cohorts had 3.0% and 1.6% 90-day hospital admission rates (relative risk 0.545; 0.154, 1.931, P =.40), and 15.3% and 7.0% composite complication rates, respectively (relative risk 0.456; 0.256, 0.812, P =.004). Conclusion: Patients enrolled on an automated DPE platform after hip and knee arthroplasties demonstrated a significant reduction in potentially avoidable 90-day costs, a 45.4% nonsignificant relative reduction in 90-day hospital admissions, and a 54.4% significant relative reduction in 90-day complications. AU - Rosner, Benjamin I. AU - Gottlieb, Marc AU - Anderson, William N. DO - 10.1016/j.arth.2017.11.036 IS - 4 KW - complications KW - comprehensive care for joint replacement KW - costs KW - readmissions KW - remote monitoring KW - value-based care PY - 2018 SP - 988 EP - 996.e4 TI - Effectiveness of an Automated Digital Remote Guidance and Telemonitoring Platform on Costs, Readmissions, and Complications After Hip and Knee Arthroplasties T2 - Journal of Arthroplasty VL - 33 ER - TY - JOUR AB - Purpose: The aims of our study are: to explore rehospitalization in mental health services across Italian regions, Local Health Districts (LHDs), and hospitals; to examine the predictive power of different clinical and organizational factors. Methods: The data set included adult patients resident in Italy discharged from a general hospital episode with a main psychiatric diagnosis in 2012. Independent variables at the individual, hospital, LHD, and region levels were used. Outcome variables were individual-level readmission and LHD-level readmission rate to any hospital at 1-year follow-up. The association with readmission of each variable was assessed through both single- and multi-level logistic regression; descriptive statistics were provided to assess geographical variation. Relevance of contextual effects was investigated through a series of random-effects regressions without covariates. Results: The national 1-year readmission rate was 43.0%, with a cross-regional coefficient of variation of 6.28%. Predictors of readmission were: admission in the same LHD as residence, psychotic disorder, higher length of stay (LoS), higher rate of public beds in the LHD; protective factors were: young age, involuntary admission, and intermediate number of public healthcare staff at the LHD level. Contextual factors turned out to affect readmission only to a limited degree. Conclusions: Homogeneity of readmission rates across regions, LHDs, hospitals, and groups of patients may be considered as a positive feature in terms of equity of the mental healthcare system. Our results highlight that readmission is mainly determined by individual-level factors. Future research is needed to better explore the relationship between readmission and LoS, discharge decision, and resource availability. AU - Tedeschi, Federico AU - Donisi, V. AU - Salazzari, D. AU - Cresswell-Smith, J. AU - Wahlbeck, K. AU - Amaddeo, F. DO - 10.1007/s00127-019-01766-y IS - 2 KW - Contextual variation KW - Hospital readmission KW - Psychiatric patients KW - Random effects PB - Springer Berlin Heidelberg PY - 2020 SN - 0123456789 SP - 187 EP - 196 TI - Clinical and organizational factors predicting readmission for mental health patients across Italy T2 - Social Psychiatry and Psychiatric Epidemiology UR - https://doi.org/10.1007/s00127-019-01766-y VL - 55 ER - TY - JOUR AB - Background: IntelliCare is a mental health app platform with 14 apps that are elemental, simple and brief to use, and eclectic. Although a variety of apps may improve engagement, leading to better outcomes, they may require navigation aids such as recommender systems that can quickly direct a person to a useful app. Objective: As the first step toward developing navigation and recommender tools, this study explored app-use patterns across the IntelliCare platform and their relationship with depression and anxiety outcomes. Methods: This is a secondary analysis of the IntelliCare Field Trial, which recruited people with depression or anxiety. Participants of the trial received 8 weeks of coaching, primarily by text, and weekly random recommendations for apps. App-use metrics included frequency and lifetime use. Depression and anxiety, measured using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7, respectively, were assessed at baseline and end of treatment. Cluster analysis was utilized to determine patterns of app use; ordinal logistic regression models and log-rank tests were used to determine if these use metrics alone, or in combination, predicted improvement or remission in depression or anxiety. Results: The analysis included 96 people who generally followed recommendations to download and try new apps each week. Apps were clustered into 5 groups: Thinking (apps that targeted or relied on thinking), Calming (relaxation and insomnia), Checklists (apps that used checklists), Activity (behavioral activation and activity), and Other. Both overall frequency of use and lifetime use predicted response for depression and anxiety. The Thinking, Calming, and Checklist clusters were associated with improvement in depression and anxiety, and the Activity cluster was associated with improvement in Anxiety only. However, the use of clusters was less strongly associated with improvement than individual app use. Conclusions: Participants in the field trial remained engaged with a suite of apps for the full 8 weeks of the trial. App-use patterns did fall into clusters, suggesting that some knowledge about the use of one app may be useful in selecting another app that the person is more likely to use and may help suggest apps based on baseline symptomology and personal preference. AU - Kwasny, Mary J. AU - Schueller, Stephen M. AU - Lattie, Emily AU - Gray, Elizabeth L. AU - Mohr, David C. DO - 10.2196/11572 IS - 3 KW - Anxiety KW - Depression KW - Mobile apps KW - Mobile phone PY - 2019 SP - 1 EP - 14 TI - Exploring the use of multiple mental health apps within a platform: Secondary analysis of the intellicare field trial T2 - Journal of Medical Internet Research VL - 21 ER - TY - JOUR AB - Firstly, the flow fields downstream one axisymmetric nozzles and a nozzle with four tabs were simulated with four different turbulent models, and the results were compared with experimental data. Then the flow fields downstream nozzles with tabs of varied orientation angles were predicted for different orientation angles of the tabs while the projected blockage of tabs was kept unchanged. The predictions were also compared with that of the nozzle without tabs. The decrease of potential core length was remarkable when tabs were affixed. As the orientation angle increased, the potential core length decreased firstly and then increased. The streamwise vortices strength increased straightly with the orientation angle. Both entrainment gain and thrust losses of the nozzles decreased as the orientation angle increased. AU - Chandrashekar, Pooja DO - 10.21037/mhealth.2018.03.02 PY - 2018 SP - 6 EP - 6 TI - Do mental health mobile apps work: evidence and recommendations for designing high-efficacy mental health mobile apps T2 - mHealth VL - 4 ER - TY - GEN TI - ab0fa4febfde82999dd5ef8b55a1c1da2766cae9 @ www.ncbi.nlm.nih.gov ER - TY - GEN AB - Background: There is a critical need for real-time tracking of behavioral indicators of mental disorders. Mobile sensing platforms that objectively and noninvasively collect, store, and analyze behavioral indicators have not yet been clinically validated or scalable. Objective: The aim of our study was to report on models of clinical symptoms for post-traumatic stress disorder (PTSD) and depression derived from a scalable mobile sensing platform. Methods: A total of 73 participants (67% [49/73] male, 48% [35/73] non-Hispanic white, 33% [24/73] veteran status) who reported at least one symptom of PTSD or depression completed a 12-week field trial. Behavioral indicators were collected through the noninvasive mobile sensing platform on participants' mobile phones. Clinical symptoms were measured through validated clinical interviews with a licensed clinical social worker. A combination hypothesis and data-driven approach was used to derive key features for modeling symptoms, including the sum of outgoing calls, count of unique numbers texted, absolute distance traveled, dynamic variation of the voice, speaking rate, and voice quality. Participants also reported ease of use and data sharing concerns. Results: Behavioral indicators predicted clinically assessed symptoms of depression and PTSD (cross-validated area under the curve [AUC] for depressed mood=.74, fatigue=.56, interest in activities=.75, and social connectedness=.83). Participants reported comfort sharing individual data with physicians (Mean 3.08, SD 1.22), mental health providers (Mean 3.25, SD 1.39), and medical researchers (Mean 3.03, SD 1.36). Conclusions: Behavioral indicators passively collected through a mobile sensing platform predicted symptoms of depression and PTSD. The use of mobile sensing platforms can provide clinically validated behavioral indicators in real time; however, further validation of these models and this platform in large clinical samples is needed. AU - Place, Skyler AU - Blanch-Hartigan, Danielle AU - Rubin, Channah AU - Gorrostieta, Cristina AU - Mead, Caroline AU - Kane, John AU - Marx, Brian P. AU - Feast, Joshua AU - Deckersbach, Thilo AU - Pentland, Alex AU - Nierenberg, Andrew AU - Azarbayejani, Ali DO - 10.2196/jmir.6678 IS - 3 KW - Behavioral symptoms KW - Depression KW - MHealth KW - Post-traumatic stress disorders PY - 2017 TI - Behavioral indicators on a mobile sensing platform predict clinically validated psychiatric symptoms of mood and anxiety disorders T2 - Journal of Medical Internet Research VL - 19 ER - TY - GEN AB - Importance: Biologic systems involved in the regulation of motor activity are intricately linked with other homeostatic systems such as sleep, feeding behavior, energy, and mood. Mobile monitoring technology (eg, actigraphy and ecological momentary assessment devices) allows the assessment of these multiple systems in real time. However, most clinical studies of mental disorders that use mobile devices have not focused on the dynamic associations between these systems. Objectives: To examine the directional associations among motor activity, energy, mood, and sleep using mobile monitoring in a community-identified sample, and to evaluate whether these within-day associations differ between people with a history of bipolar or other mood disorders and controls without mood disorders. Design, Setting, and Participants: This study used a nested case-control design of 242 adults, a subsample of a community-based sample of adults. Probands were recruited by mail from the greater Washington, DC, metropolitan area from January 2005 to June 2013. Enrichment of the sample for mood disorders was provided by volunteers or referrals from the National Institutes of Health Clinical Center or by participants in the National Institute of Mental Health Mood and Anxiety Disorders Program. The inclusion criteria were the ability to speak English, availability to participate, and consent to contact at least 2 living first-degree relatives. Data analysis was performed from June 2013 through July 2018. Main Outcomes and Measures: Motor activity and sleep duration data were obtained from minute-to-minute activity counts from an actigraphy device worn on the nondominant wrist for 2 weeks. Mood and energy levels were assessed by subjective analogue ratings on the ecological momentary assessment (using a personal digital assistant) by participants 4 times per day for 2 weeks. Results: Of the total 242 participants, 92 (38.1%) were men and 150 (61.9%) were women, with a mean (SD) age of 48 (16.9) years. Among the participants, 54 (22.3%) had bipolar disorder (25 with bipolar I; 29 with bipolar II), 91 (37.6%) had major depressive disorder, and 97 (40.1%) were controls with no history of mood disorders. A unidirectional association was found between motor activity and subjective mood level (β = -0.018, P =.04). Bidirectional associations were observed between motor activity (β = 0.176; P =.03) and subjective energy level (β = 0.027; P =.03) as well as between motor activity (β = -0.027; P =.04) and sleep duration (β = -0.154; P =.04). Greater cross-domain reactivity was observed in bipolar disorder across all outcomes, including motor activity, sleep, mood, and energy. Conclusions and Relevance: These findings suggest that interventions focused on motor activity and energy may have greater efficacy than current approaches that target depressed mood; both active and passive tracking of multiple regulatory systems are important in designing therapeutic targets.. AU - Merikangas, Kathleen Ries AU - Swendsen, Joel AU - Hickie, Ian B. AU - Cui, Lihong AU - Shou, Haochang AU - Merikangas, Alison K. AU - Zhang, Jihui AU - Lamers, Femke AU - Crainiceanu, Ciprian AU - Volkow, Nora D. AU - Zipunnikov, Vadim DO - 10.1001/jamapsychiatry.2018.3546 IS - 2 PY - 2019 SP - 190 EP - 198 TI - Real-time Mobile Monitoring of the Dynamic Associations among Motor Activity, Energy, Mood, and Sleep in Adults with Bipolar Disorder T2 - JAMA Psychiatry VL - 76 ER - TY - JOUR AB - Background: The initial introduction of the World Wide Web in 1990 brought around the biggest change in information acquisition. Due to the abundance of devices and ease of access they subsequently allow, the utility of mobile health (mHealth) has never been more endemic. A substantial amount of interactive and psychoeducational apps are readily available to download concerning a wide range of health issues. mHealth has the potential to reduce waiting times for appointments; eradicate the need to meet in person with a clinician, successively diminishing the workload of mental health professionals; be more cost effective to practices; and encourage self-care tactics. Previous research has given valid evidence with empirical studies proving the effectiveness of physical and mental health interventions using mobile apps. Alongside apps, there is evidence to show that receiving short message service (SMS) messages, which entail psychoeducation, medication reminders, and links to useful informative Web pages can also be advantageous to a patient's mental and physical well-being. Available mHealth apps and SMS services and their ever improving quality necessitates a systematic review in the area in reference to reduction of symptomology, adherence to intervention, and usability. Objective: The aim of this review was to study the efficacy, usability, and feasibility of mobile apps and SMS messages as mHealth interventions for self-guided care. Methods: A systematic literature search was carried out in JMIR, PubMed, PsychINFO, PsychARTICLES, Google Scholar, MEDLINE, and SAGE. The search spanned from January 2008 to January 2017. The primary outcome measures consisted of weight management, (pregnancy) smoking cessation, medication adherence, depression, anxiety and stress. Where possible, adherence, feasibility, and usability outcomes of the apps or SMS services were evaluated. Between-group and within-group effect sizes (Cohen d) for the mHealth intervention method group were determined. Results: A total of 27 studies, inclusive of 4658 participants were reviewed. The papers included randomized controlled trials (RCTs) (n=19), within-group studies (n=7), and 1 within-group study with qualitative aspect. Studies show improvement in physical health and significant reductions of anxiety, stress, and depression. Within-group and between-group effect sizes ranged from 0.05-3.37 (immediately posttest), 0.05-3.25 (1-month follow-up), 0.08-3.08 (2-month follow-up), 0.00-3.10 (3-month follow-up), and 0.02-0.27 (6-month follow-up). Usability and feasibility of mHealth interventions, where reported, also gave promising, significant results. Conclusions: The review shows the promising and emerging efficacy of using mobile apps and SMS text messaging as mHealth interventions. AU - Rathbone, Amy Leigh AU - Prescott, Julie DO - 10.2196/jmir.7740 IS - 8 KW - Health KW - Intervention study KW - MHealth KW - Portable electronic applications KW - Review KW - Short message service KW - Smartphone KW - Systematic KW - Treatment efficacy PY - 2017 SP - 1 EP - 24 TI - The use of mobile apps and SMS messaging as physical and mental health interventions: Systematic review T2 - Journal of Medical Internet Research VL - 19 ER - TY - JOUR AB - Background: People with serious mental illness (SMI) have significant unmet mental health needs. Development and testing of digital interventions that can alleviate the suffering of people with SMI is a public health priority. Objective: The aim of this study is to conduct a fully remote randomized waitlist-controlled trial of CORE, a smartphone intervention that comprises daily exercises designed to promote reassessment of dysfunctional beliefs in multiple domains. Methods: Individuals were recruited via the web using Google and Facebook advertisements. Enrolled participants were randomized into either active intervention or waitlist control groups. Participants completed the Beck Depression Inventory-Second Edition (BDI-II), Generalized Anxiety Disorder-7 (GAD-7), Hamilton Program for Schizophrenia Voices, Green Paranoid Thought Scale, Recovery Assessment Scale (RAS), Rosenberg Self-Esteem Scale (RSES), Friendship Scale, and Sheehan Disability Scale (SDS) at baseline (T1), 30-day (T2), and 60-day (T3) assessment points. Participants in the active group used CORE from T1 to T2, and participants in the waitlist group used CORE from T2 to T3. Both groups completed usability and accessibility measures after they concluded their intervention periods. Results: Overall, 315 individuals from 45 states participated in this study. The sample comprised individuals with self-reported bipolar disorder (111/315, 35.2%), major depressive disorder (136/315, 43.2%), and schizophrenia or schizoaffective disorder (68/315, 21.6%) who displayed moderate to severe symptoms and disability levels at baseline. Participants rated CORE as highly usable and acceptable. Intent-to-treat analyses showed significant treatment×time interactions for the BDI-II (F1,313=13.38; P<.001), GAD-7 (F1,313=5.87; P=.01), RAS (F1,313=23.42; P<.001), RSES (F1,313=19.28; P<.001), and SDS (F1,313=10.73; P=.001). Large effects were observed for the BDI-II (d=0.58), RAS (d=0.61), and RSES (d=0.64); a moderate effect size was observed for the SDS (d=0.44), and a small effect size was observed for the GAD-7 (d=0.20). Similar changes in outcome measures were later observed in the waitlist control group participants following crossover after they received CORE (T2 to T3). Approximately 41.5% (64/154) of participants in the active group and 60.2% (97/161) of participants in the waitlist group were retained at T2, and 33.1% (51/154) of participants in the active group and 40.3% (65/161) of participants in the waitlist group were retained at T3. Conclusions: We successfully recruited, screened, randomized, treated, and assessed a geographically dispersed sample of participants with SMI entirely via the web, demonstrating that fully remote clinical trials are feasible in this population; however, study retention remains challenging. CORE showed promise as a usable, acceptable, and effective tool for reducing the severity of psychiatric symptoms and disability while improving recovery and self-esteem. Rapid adoption and real-world dissemination of evidence-based mobile health interventions such as CORE are needed if we are to shorten the science-to-service gap and address the significant unmet mental health needs of people with SMI during the COVID-19 pandemic and beyond. AU - Ben-Zeev, Dror AU - Chander, Ayesha AU - Tauscher, Justin AU - Buck, Benjamin AU - Nepal, Subigya AU - Campbell, Andrew AU - Doron, Guy DO - 10.2196/29201 IS - 11 KW - Bipolar disorder KW - Depression KW - Mobile health KW - Mobile phone KW - Schizophrenia PY - 2021 TI - A smartphone intervention for people with serious mental illness: Fully remote randomized controlled trial of CORE T2 - Journal of Medical Internet Research VL - 23 ER - TY - JOUR AB - Background: Mobile health (mHealth) applications provide new methods of engagement with patients and can help patients manage their mental health condition. Objective: The main objective of this study is to explore the prevalence of the use of mobile health applications for mental health patients in Saudi Arabia. Methods: A total of 376 participants with depression and/or anxiety completed an online survey distributed by social networks which asked questions relating to mobile phone ownership, uses of health applications, and utilization patterns to track mental health related issues. Results: Approximately, 46% of the participants reported running one or two healthcare related applications on their mobile phones. In all age groups, 64% of the participants used their mobile phones to access information related to their own health. Also, 64% of the participants expressed interest in using their own mobile phones to track and follow the progression of their depression and/or anxiety. Conclusions: Developing mobile health applications for Saudi mental health patients is needed since it can offer opportunities for patients, researchers, caregivers, and legislators to work together to improve the state of mental health care in Saudi Arabia. AU - Atallah, Nora AU - Khalifa, Mohamed AU - El Metwally, Ashraf AU - Househ, Mowafa DO - 10.1016/j.cmpb.2017.12.002 KW - Engaging and enabling patients KW - Mental health KW - Mobile applications KW - Saudi Arabia PB - Elsevier Ireland Ltd PY - 2018 SP - 163 EP - 168 TI - The prevalence and usage of mobile health applications among mental health patients in Saudi Arabia T2 - Computer Methods and Programs in Biomedicine UR - https://doi.org/10.1016/j.cmpb.2017.12.002 VL - 156 ER - TY - JOUR AB - Objective: Despite the potential benefits of mobile mental health apps, real-world results indicate engagement issues because of low uptake and sustained use. This review examined how studies have measured and reported on user engagement indicators (UEIs) for mental health apps. Methods: A systematic review of multiple databases was performed in July 2018 for studies of mental health apps for depression, bipolar disorder, schizophrenia, and anxiety that reported on UEIs, namely usability, user satisfaction, acceptability, and feasibility. The subjective and objective criteria used to assess UEIs, among other data, were extracted from each study. Results: Of 925 results, 40 studies were eligible. Every study reported positive results for the usability, satisfaction, acceptability, or feasibility of the app. Of the 40 studies, 36 (90%) employed 371 indistinct subjective criteria that were assessed with surveys, interviews, or both, and 23 studies used custom subjective scales, rather than preexisting standardized assessment tools. A total of 25 studies (63%) used objective criteria - with 71 indistinct measures. No two studies used the same combination of subjective or objective criteria to assess UEIs of the app. Conclusions: The high heterogeneity and use of custom criteria to assess mental health apps in terms of usability, user satisfaction, acceptability, or feasibility present a challenge for understanding real-world low uptake of these apps. Every study reviewed claimed that UEIs for the app were rated highly, which suggests a need for the field to focus on engagement by creating reporting standards and more carefully considering claims. AU - Ng, Michelle M. AU - Firth, Joseph AU - Minen, Mia AU - Torous, John DO - 10.1176/appi.ps.201800519 IS - 7 PY - 2019 SP - 538 EP - 544 TI - User engagement in mental health apps: A review of measurement, reporting, and validity T2 - Psychiatric Services VL - 70 ER - TY - GEN TI - technology-and-the-future-of-mental-health-treatment @ www.nimh.nih.gov UR - https://www.nimh.nih.gov/health/topics/technology-and-the-future-of-mental-health-treatment ER - TY - JOUR AB - Exacerbations of COPD are one of the commonest causes of admission and readmission to hospital. The role of digital interventions to support self-management in improving outcomes is uncertain. We conducted an open, randomised controlled trial of a digital health platform application (app) in 41 COPD patients recruited following hospital admission with an acute exacerbation. Subjects were randomised to either receive usual care, including a written self-management plan (n = 21), or the myCOPD app (n = 20) for 90 days. The primary efficacy outcome was recovery rate of symptoms measured by COPD assessment test (CAT) score. Exacerbations, readmission, inhaler technique quality of life and patient activation (PAM) scores were also captured by a blinded team. The app was acceptable in this care setting and was used by 17 of the 20 patients with sustained use over the study period. The treatment effect on the CAT score was 4.49 (95% CI: −8.41, −0.58) points lower in the myCOPD arm. Patients’ inhaler technique improved in the digital intervention arm (101 improving to 20 critical errors) compared to usual care (100 to 72 critical errors). Exacerbations tended to be less frequent in the digital arm compared to usual care; 34 vs 18 events. Hospital readmissions risk was numerically lower in the digital intervention arm: OR for readmission 0.383 (95% CI: 0.074, 1.987; n = 35). In this feasibility study of the digital self-management platform myCOPD, the app has proven acceptable to patients to use and use has improved exacerbation recovery rates, with strong signals of lower re-exacerbation and readmission rates over 90 days. myCOPD reduced the number of critical errors in inhaler technique compared to usual care with written self-management. This provides a strong basis for further exploration of the use of app interventions in the context of recently hospitalised patients with COPD and informs the potential design of a large multi-centre trial. AU - North, Mal AU - Bourne, Simon AU - Green, Ben AU - Chauhan, Anoop J. AU - Brown, Tom AU - Winter, Jonathan AU - Jones, Tom AU - Neville, Dan AU - Blythin, Alison AU - Watson, Alastair AU - Johnson, Matthew AU - Culliford, David AU - Elkes, Jack AU - Cornelius, Victoria AU - Wilkinson, Tom M.A. DO - 10.1038/s41746-020-00347-7 IS - 1 PB - Springer US PY - 2020 SP - 1 EP - 8 TI - A randomised controlled feasibility trial of E-health application supported care vs usual care after exacerbation of COPD: the RESCUE trial T2 - npj Digital Medicine UR - http://dx.doi.org/10.1038/s41746-020-00347-7 VL - 3 ER - TY - JOUR AU - Anthes, E. PY - 2016 SP - 1 EP - 4 TI - Pocket Psychiatry Apps Have Exploded T2 - Nature VL - 532 ER - TY - JOUR AB - Background: Promoting well-being and preventing poor mental health in young people is a major global priority. Building emotional competence skills via a mobile app may be an effective, scalable and acceptable way to do this. A particular risk factor for anxiety and depression is elevated worry and rumination (repetitive negative thinking, RNT). An app designed to reduce RNT may prevent future incidence of depression and anxiety. Method/design: The Emotional Competence for Well-Being in Young Adults study developed an emotional competence app to be tested via randomised controlled trials in a longitudinal prospective cohort. This off-shoot study adapts the app to focus on targeting RNT (worry, rumination), known risk factors for poor mental health. In this study, 16–24 year olds in the UK, who report elevated worry and rumination on standardised questionnaires are randomised to (i) receive the RNT-targeting app immediately for 6 weeks (ii) a waiting list control who receive the app after 6 weeks. In total, the study will aim to recruit 204 participants, with no current diagnosis of major depression, bipolar disorder or psychosis, across the UK. Assessments take place at baseline (pre-randomisation), 6 and 12 weeks post-randomisation. Primary endpoint and outcome for the study is level of rumination assessed on the Rumination Response Styles Questionnaire at 6 weeks. Worry, depressive symptoms, anxiety symptoms and well-being are secondary outcomes. Compliance, adverse events and potentially mediating variables will be carefully monitored. Discussion: This trial aims to better understand the benefits of tackling RNT via an mobile phone app intervention in young people. This prevention mechanism trial will establish whether targeting worry and rumination directly via an app provides a feasible approach to prevent depression and anxiety, with scope to become a widescale public health strategy for preventing poor mental health and promoting well-being in young people. Trial registration: ClinicalTrials.gov, NCT04950257. Registered 6 July 2021 – Retrospectively registered. AU - Edge, Daniel AU - Newbold, Alexandra AU - Ehring, Thomas AU - Rosenkranz, Tabea AU - Frost, Mads AU - Watkins, Edward R. DO - 10.1186/s12888-021-03536-0 IS - 1 KW - Cognitive behavioral therapy KW - Depression KW - Emotional competence KW - Mobile-health KW - Prevention KW - Randomised controlled trial KW - Rumination KW - Well-being KW - Worry KW - Young people PB - BMC Psychiatry PY - 2021 SP - 1 EP - 10 TI - Reducing worry and rumination in young adults via a mobile phone app: study protocol of the ECoWeB (Emotional Competence for Well-Being in Young Adults) randomised controlled trial focused on repetitive negative thinking T2 - BMC Psychiatry VL - 21 ER - TY - JOUR AB - Background: Mental health apps (MHAs) provide opportunities for accessible, immediate, and innovative approaches to better understand and support the treatment of mental health disorders, especially those with a high burden, such as bipolar disorder (BD). Many MHAs have been developed, but few have had their effectiveness evaluated. Objective: This systematic scoping review explores current process and outcome measures of MHAs for BD with the aim to provide a comprehensive overview of current research. This will identify the best practice for evaluating MHAs for BD and inform future studies. Methods: A systematic literature search of the health science databases PsycINFO, MEDLINE, Embase, EBSCO, Scopus, and Web of Science was undertaken up to January 2021 (with no start date) to narratively assess how studies had evaluated MHAs for BD. Results: Of 4051 original search results, 12 articles were included. These 12 studies included 435 participants, and of these, 343 had BD type I or II. Moreover, 11 of the 12 studies provided the ages (mean 37 years) of the participants. One study did not report age data. The male to female ratio of the 343 participants was 137:206. The most widely employed validated outcome measure was the Young Mania Rating Scale, being used 8 times. The Hamilton Depression Rating Scale-17/Hamilton Depression Rating Scale was used thrice; the Altman Self-Rating Mania Scale, Quick Inventory of Depressive Symptomatology, and Functional Assessment Staging Test were used twice; and the Coping Inventory for Stressful Situations, EuroQoL 5-Dimension Health Questionnaire, Generalized Anxiety Disorder Scale-7, Inventory of Depressive Symptomatology, Mindfulness Attention Awareness Scale, Major Depression Index, Morisky-Green 8-item, Perceived Stress Scale, and World Health Organization Quality of Life-BREF were used once. Self-report measures were captured in 9 different studies, 6 of which used MONARCA. Mood and energy levels were the most commonly used self-report measures, being used 4 times each. Furthermore, 11 of the 12 studies discussed the various confounding factors and barriers to the use of MHAs for BD. Conclusions: Reported low adherence rates, usability challenges, and privacy concerns act as barriers to the use of MHAs for BD. Moreover, as MHA evaluation is itself developing, guidance for clinicians in how to aid patient choices in mobile health needs to develop. These obstacles could be ameliorated by incorporating co-production and co-design using participatory patient approaches during the development and evaluation stages of MHAs for BD. Further, including qualitative aspects in trials that examine patient experience of both mental ill health and the MHA itself could result in a more patient-friendly fit-for-purpose MHA for BD. AU - Tatham, Iona AU - Clarke, Ellisiv AU - Grieve, Kelly Ann AU - Kaushal, Pulkit AU - Smeddinck, Jan AU - Millar, Evelyn Barron AU - Sharma, Aditya Narain DO - 10.2196/29114 IS - 3 KW - bipolar disorder KW - child and adolescent mental health KW - mental health KW - scoping review PY - 2022 SP - 1 EP - 18 TI - Process and Outcome Evaluations of Smartphone Apps for Bipolar Disorder: Scoping Review T2 - Journal of Medical Internet Research VL - 24 ER - TY - JOUR AB - Over 50% of people diagnosed with a severe mental illness, such as schizophrenia or bipolar disorder, will meet criteria for a substance use disorder in their lifetime. This dual disorder often starts during youth and leads to significant societal costs, including lower employability rates, more hospitalizations, and higher risk of homelessness and of suicide attempts when compared to those with a serious mental illness without substance misuse. Moreover, many individuals presenting with comorbid disorders also present with other psychological difficulties as well, such as personality disorders or anxiety and depression, also known as complex comorbid disorders. Transdiagnostic treatments that focus on core difficulties found in people with complex dual disorders, such as emotional regulation, are direly needed. Emotional regulation skills can help reduce distress related to psychotic symptoms and maintain abstinence in substance use disorders. New technologies in the field of communications have developed considerably over the past decade and have the potential to improve access to such treatments, a major problem in many health care settings. As such, this paper aims at: presenting core difficulties present in many individuals with dual disorders, reviewing the scientific literature pertaining to the use of mobile applications in mental health and addictions, and presenting the development and potential of a new application for emotional regulation for people with dual disorders. AU - Pennou, Antoine AU - Lecomte, Tania AU - Potvin, Stéphane AU - Khazaal, Yasser DO - 10.3389/fpsyt.2019.00302 IS - MAY KW - Dual disorders KW - Emotion regulation KW - Mental health apps KW - Psychosis KW - Schizophrenia KW - Severe mental illness KW - Substance use disorder PY - 2019 SP - 1 EP - 11 TI - Mobile intervention for individuals with psychosis, dual disorders, and their common comorbidities: A literature review T2 - Frontiers in Psychiatry VL - 10 ER - TY - JOUR AB - Background and Aims—Cardiovascular disease (CVD) is among the leading causes of morbidity and mortality worldwide. Traditional risk factors predict 75-80% of an individual's risk of incident CVD. However, the role of early life experiences in future disease risk is gaining attention. The Barker hypothesis proposes fetal origins of adult disease, with consistent evidence demonstrating the deleterious consequences of birth weight outside the normal range. In this study, we investigate the role of birth weight in CVD risk prediction. Methods and Results—The Women's Health Initiative (WHI) represents a large national cohort of post-menopausal women with 63 815 participants included in this analysis. Univariable proportional hazards regression analyses evaluated the association of 4 self-reported birth weight categories against 3 CVD outcome definitions, which included indicators of coronary heart disease, ischemic stroke, coronary revascularization, carotid artery disease and peripheral arterial disease. The role of birth weight was also evaluated for prediction of CVD events in the presence of traditional risk factors using 3 existing CVD risk prediction equations: one body mass index (BMI)-based and two laboratory-based models. Low birth weight (LBW) (< 6 lbs.) was significantly associated with all CVD outcome definitions in univariable analyses (HR=1.086, p=0.009). LBW was a significant covariate in the BMI-based model (HR=1.128, p<0.0001) but not in the lipid-based models. Conclusion—LBW (<6 lbs.) is independently associated with CVD outcomes in the WHI cohort. This finding supports the role of the prenatal and postnatal environment in contributing to the development of adult chronic disease. AU - Ogura, Yuji AU - Parsons, William H AU - Kamat, Siddhesh S AU - Cravatt, Benjamin F DO - 10.1176/appi.ps.201800519.User IS - 10 KW - asian americans KW - depression KW - osteoarthritis KW - pain KW - quantitative sensory testing PY - 2017 SP - 139 EP - 148 TI - 乳鼠心肌提取 HHS Public Access T2 - Physiology & behavior UR - file:///C:/Users/Carla Carolina/Desktop/Artigos para acrescentar na qualificação/The impact of birth weight on cardiovascular disease risk in the.pdf VL - 176 ER - TY - JOUR AU - Pros, The AU - Apps, Evaluating SP - 22 EP - 24 TI - Technology and the Future of Mental Health Treatment Introduction The Pros and Cons of Mental Health Apps Current Trends in App Development Research via Smartphone ? A New Partnership : Clinicians and Engineers Evaluating Apps What is NIMH ’ s Role in Men ER - TY - JOUR AB - Background: Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity. Objective: To assess (i) acceptability of continuous monitoring to SMI patients and health professionals over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; and (iii) the feasibility of detecting early warning signs of relapse. Methods: The active symptom monitoring smartphone app was built into an end-to-end system in two NHS Trusts to enable real-time symptom self-monitoring and detection by the clinical team of early signs of relapse in people with severe mental illness. We conducted an open randomized controlled trial of active symptom monitoring compared to usual management to assess: (i) acceptability and safety of continuous monitoring over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; (iii) feasibility of detecting early warning signs of relapse communicated to the healthcare staff via an app streaming data to the electronic health record. Eligible participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of schizophrenia and related disorders, and a history of relapse within the previous two years were enrolled from an early intervention team and a community mental health team. Results: Of 181 eligible patients, 81 (45%) consented and were randomized to either active symptom monitoring or management as usual. At 12 weeks, 90% (33/36) of those in the active monitoring group continued to use the system and exhibited an adherence rate (defined as responding to >33% of alerts) of 84% (30/36}. Active symptom monitoring was associated with no difference on the empowerment scale in comparison to the usual management group at 12 weeks. The pre-planned intent-to-treat analysis of the primary outcome, a positive score on the Positive and Negative Syndrome Scale (PANSS) scale, showed a significant reduction in the active symptom monitoring group over 12 weeks in the early intervention center. Alerts for personalized early warning signs of relapse were built into the workflows of both NHS Trusts, and 100% of health professional staff used the system in a new digital workflow. Qualitative analyses supported the acceptability of the system to participants and staff. Conclusions: The active smartphone monitoring system is feasible and was accepted by users in a 3-month study of people with severe mental illness, with surprisingly high levels of adherence. App use was associated with psychotic symptom improvement in recent-onset participants, but not those with longstanding illness, supporting the notion of improved self-management. When built into clinical management workflows to enable personalized alerts of symptom deterioration, the app has demonstrated utility in promoting earlier intervention for relapse. AU - Lewis, Shon AU - Ainsworth, John AU - Sanders, Caroline AU - Stockton-Powdrell, Charlotte AU - Machin, Matthew AU - Whelan, Pauline AU - Hopkins, Richard AU - He, Zhimin AU - Applegate, Eve AU - Drake, Richard AU - Bamford, Charlie AU - Roberts, Chris AU - Wykes, Til DO - 10.2196/17019 IS - 8 KW - Digital KW - Mental health KW - Psychosis KW - Self management KW - Smartphone KW - m-health PY - 2020 TI - Smartphone-enhanced symptom management in psychosis: Open, randomized controlled trial T2 - Journal of Medical Internet Research VL - 22 ER - TY - GEN AB - Seiring dengan kemajuan ilmu pengetahuan dan teknologi yang menjadi pusat perhatian dunia. Maka manusia dituntut untuk menciptakan peralatan-peralatan canggih untuk teknologi muktahir. Baik itu dalam bidang bisnis, perdagangan, kesehatan, militer, pendidikan, komunikasi dan budaya maupun bidang-bidang lainnya. Maka teknologi ini membawa perubahan pada peralatan-peralatan yang dulunya bekerja secara analog mulai dikembangkan secara digital, dan bahkan yang bekerjanya secara manual sekarang banyak dikembangkan secara otomatis, seperti kamera digital, handycam, dan sebagainya, dalam pembacaan pengukuran juga sudah dikembangkan ke dalam teknik digital. Contohnya perangkat Load Cell. Dan keuntungan menggunakan Load Cell adalah untuk mempermudah dalam pembacaan data untuk meminimalkan kesalahan dalam pembacaan data yang disebabkan adanya human error.Pada pemilihan Load Cell bertujuan untuk memilih kecocokan dalam membuat rancang bangun alat uji tarik kapasitas 3 ton, dimana dalam pemilihan ini kami memilih jenis load cell “S” karna alat yang kita rancang adalah uji tarik bukan uji tekan. Dengan kapasitas load cell 5 ton. Untuk membuat jarak aman dalam pengujian specimen ST41. Load Cell menggunakan system perangkat elektronik pengolahan data yang menjadi sebuah kurva tegangan regangan. Data-data yang diperoleh tersebut berupa besarnya pembebanan hasil dari pengujian specimen ST41. Kata AU - Maros, Hikmah AU - Juniar, Sarah PY - 2016 SN - 2013206534 SP - 1 EP - 23 TI - 済無No Title No Title No Title T2 - Technology and the Future of Mental Health Treatment ER - TY - GEN AU - NIMH PY - 2019 TI - No Title T2 - Technology and the Future of Mental Health Treatment UR - https://www.nimh.nih.gov/health/topics/technology-and-the-future-of-mental-health-treatment ER - TY - GEN AB - A mental disorder is characterized by a clinically significant disturbance in an individual’s cognition, emotional regulation, or behaviour. It is usually associated with distress or impairment in important areas of functioning. There are many different types of mental disorders. Mental disorders may also be referred to as mental health conditions. The latter is a broader term covering mental disorders, psychosocial disabilities and (other) mental states associated with significant distress, impairment in functioning, or risk of self-harm. This fact sheet focuses on mental disorders as described by the International Classification of Diseases 11th Revision (ICD-11). In 2019, 1 in every 8 people, or 970 million people around the world were living with a mental disorder, with anxiety and depressive disorders the most common (1). In 2020, the number of people living with anxiety and depressive disorders rose significantly because of the COVID-19 pandemic. Initial estimates show a 26% and 28% increase respectively for anxiety and major depressive disorders in just one year (2). While effective prevention and treatment options exist, most people with mental disorders do not have access to effective care. Many people also experience stigma, discrimination and violations of human rights. AU - WHO PY - 2022 TI - No Title T2 - Mental disorders UR - https://www.who.int/en/news-room/fact-sheets/detail/mental-disorders ER - TY - GEN AB - En la actualidad, la adherencia terapéutica sigue suponiendo uno de los principales temas de estudio entre los profesionales sanitarios, ya que se trata de un fenómeno complejo que atañe variables multifactoriales. Su importancia radica en la influencia que ejerce en la evolución y el pronóstico del paciente, además una baja adherencia terapéutica implica un mayor impacto socioeconómico y un mal uso de los recursos sanitarios por complicaciones evitables. En el caso del tratamiento en pacientes psicóticos, la adherencia cobra todavía más importancia, ya que el abandono de este constituye un problema prevalente en la actualidad. En la adherencia del paciente psiquiátrico, la variable más importante a tener en cuenta es el propio paciente, concretamente su insight de enfermedad, incluyendo su comportamiento y actitudes relacionadas con el tratamiento. Es por ello que como profesionales de enfermería debemos emprender acciones enfocadas al establecimiento del tratamiento psiquiátrico, favoreciendo la adherencia y diseñando nuevas estrategias que nos permitan adaptarnos al paciente dentro de su contexto como ser holístico. AU - Roldan, Raquel Ruiz PY - 2019 SP - 1 EP - 34 TI - La adherencia al tratamiento en pacientes con trastornos psicóticos ER - TY - GEN AU - Molly K. Bailey, Audrey J. Weiss, Marguerite L. Barrett, M.S., and H. Joanna Jiang. PY - 2019 TI - Characteristics of 30-Day All-Cause Hospital Readmissions, 2010-2016 T2 - Characteristics of 30-Day All-Cause Hospital Readmissions, 2010-2016 UR - https://www.hcup-us.ahrq.gov/reports/statbriefs/sb248-Hospital-Readmissions-2010-2016.jsp ER - TY - GEN AU - Ordóñez, Ingrid PY - 2015 TI - Frecuencia y características de pacientes con reingreso temprano en el hospital mental universitario de risaralda en los años 2011 a 2013 ER - TY - JOUR AU - Moreno, Herman IS - 4 PY - 2020 TI - Análisis de costo del tratamiento de los trastornos del estado de ánimo en Colombia T2 - Archivo Venezolano de farmacologia y terapeutica. VL - 41 ER -