116 research outputs found

    Towards MARTE++ : an enhanced UML-based language to Model and Analyse Real-Time and Embedded Systems for the IoT age

    Get PDF
    This paper presents requirements for an enhanced version of the UML Profile for MARTE, the current standard of the OMG for the modelling and analysis of real-time embedded systems. Since its adoption by the OMG in 2009 and after the various additions along recent years, MARTE has been essayed in a number of application domains and validation approaches. This paper makes a review of these various efforts describing extensions, additional functionality, and modeling needs that may serve as inputs for the preparation of a formal request for proposals (RFP) at the OMG. Aspects that have been found useful to have in it include modern platforms like Multi-core, Many-core and GPUs, networking for broader domains like the Internet of Things, federation of all modelling artifacts involved in the development process, including tracing mechanisms embedded in the language to link design and run-time artifacts, and more elaborated kinds of quantitative analyses and extra functional properties, like energy and memory consumption, heat dissipation, and temperature distribution. Also methodological aspects like its specification as a profile and/or as a meta-model will need to be discussed. Finally, the standard needs to be reviewed against the new executable UML related specifications; particularly to be in alignment with those semantics of state machines and composite structures.This work receives funding from the Spanish Government under grant number TIN2014-56158-C4-2-P (M2C2), and from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 737494 (MegaM@RT2). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and Sweden, France, Spain, Italy, Finland, Czech Republic. We thank the anonymous reviewers for their insights and proposals of improvement

    X-Aute: herramienta para la automatización de las pruebas en las interfaces de usuario gráficas desarrolladas con XAML

    Get PDF
    Las pruebas automatizadas sobre interfaces de usuario se están convirtiendo en elementos indispensables para asegurar la calidad de esta parte del software, la cual cada vez está tomando más importancia, de una manera mucho más rápida, efectiva y eficaz que realizando tan sólo testeo manual. Con la automatización de los test las organizaciones pueden ahorrar gran cantidad de tiempo y recursos o producir software de mayor calidad mucho más rápido. Todo esto unido a la llegada de las nuevas interfaces de usuario gráficas WPF y a la adopción de estas como estándar para el desarrollo de las nuevas GUI en los Sistemas de Información Corporativos, hace necesario el desarrollo de una herramienta capaz de asegurar la calidad de dichas GUI, mediante un testeo automatizado. Este proyecto presenta una herramienta, X-Aute, que se basa en el framework UI Automation, a través del cual es capaz de realizar la tan necesaria automatización de pruebas sobre las interfaces de usuario gráficas WPF.Ingeniería en Informátic

    ReMindCare, an app for daily clinical practice in patients with first episode psychosis: A pragmatic real-world study protocol

    Full text link
    [EN] Aim Despite the potential benefits of e-health interventions for patients with psychosis, the integration of these applications into the clinical workflow and analysis of their long-term effects still face significant challenges. To address these issues, we developed the ReMindCare app. This app aims to improve the treatment quality for patients with psychosis. We chose to study the app in real world and pragmatic manner to ensure results will be generalizable. Methods This is a naturalistic empirical study of patients in a first episode of psychosis programme. The app was purpose-designed based on two previous studies, and it offers the following assessments: (a) three daily questions regarding anxiety, sadness and irritability; and (b) 18 weekly questions about medication adherence, medication side effects, medication attitudes and prodromal symptoms. The app offers preset alerts, reminders and the ability for patients to reach out to their clinicians. Data captured by the app are linked to the electronic medical record of the patient. Patients will use the app as part of their ongoing care for a maximum period of 5 years, and assessments will occur at baseline and at the end of the first, second and fifth years of app use. Results Recruitment started in October 2018 and is still ongoing. Conclusions The ReMindCare app represents early real-world use of digital mental health tools that offer direct integration into clinical care. High retention and compliance rates are expected, and this will in turn lead to improved quality of assessments and communication between patients and clinicians.Centro de Investigacion Biomedica en Red de Salud Mental; European Social Fund, Grant/Award Number: 2017/9830; Generalitat Valenciana, Grant/Award Number: PROMETEO/2016/082; Instituto de Salud Carlos III, Grant/Award Numbers: PI01399, PI13/00447, PI17/00402Bonet, L.; Torous, J.; Arce Grilo, AD.; Blanquer Espert, I.; Sanjuán, J. (2021). ReMindCare, an app for daily clinical practice in patients with first episode psychosis: A pragmatic real-world study protocol. Early Intervention in Psychiatry. 15(1):183-192. https://doi.org/10.1111/eip.12960S183192151Abbott, P. A., Foster, J., Marin, H. de F., & Dykes, P. C. (2014). Complexity and the science of implementation in health IT—Knowledge gaps and future visions. International Journal of Medical Informatics, 83(7), e12-e22. doi:10.1016/j.ijmedinf.2013.10.009American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders. doi:10.1176/appi.books.9780890425596Appelbaum, S. H., & Wohl, L. (2000). Transformation or change: some prescriptions for health care organizations. Managing Service Quality: An International Journal, 10(5), 279-298. doi:10.1108/09604520010345768Arango, C., Bernardo, M., Bonet, P., Cabrera, A., Crespo-Facorro, B., Cuesta, M. J., … Melau, M. (2017). Cuando la asistencia no sigue a la evidencia: el caso de la falta de programas de intervención temprana en psicosis en España. Revista de Psiquiatría y Salud Mental, 10(2), 78-86. doi:10.1016/j.rpsm.2017.01.001Arango C. Crespo‐Facorro B. Cuesta M. J. González‐Pinto A. Gutiérrez J. R. Lalucat L. &Sanjuán J. Libro blanco de la atención temprana en psicosis.2018. Available at:www.sepsiq.org/file/Enlaces/Libro%20blanco%20de%20la%20Intervenci%C3%B3n%20Temprana%20en%20Espa%C3%B1a%20(2018).pdfAref-Adib, G., O’Hanlon, P., Fullarton, K., Morant, N., Sommerlad, A., Johnson, S., & Osborn, D. (2016). A qualitative study of online mental health information seeking behaviour by those with psychosis. BMC Psychiatry, 16(1). doi:10.1186/s12888-016-0952-0Barnett, I., Torous, J., Staples, P., Sandoval, L., Keshavan, M., & Onnela, J.-P. (2018). Relapse prediction in schizophrenia through digital phenotyping: a pilot study. Neuropsychopharmacology, 43(8), 1660-1666. doi:10.1038/s41386-018-0030-zBaumel, A., Faber, K., Mathur, N., Kane, J. M., & Muench, F. (2017). Enlight: A Comprehensive Quality and Therapeutic Potential Evaluation Tool for Mobile and Web-Based eHealth Interventions. Journal of Medical Internet Research, 19(3), e82. doi:10.2196/jmir.7270Beck, A. (2004). A new instrument for measuring insight: the Beck Cognitive Insight Scale. Schizophrenia Research, 68(2-3), 319-329. doi:10.1016/s0920-9964(03)00189-0Ben-Zeev, D., Brenner, C. J., Begale, M., Duffecy, J., Mohr, D. C., & Mueser, K. T. (2014). Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone Intervention for Schizophrenia. Schizophrenia Bulletin, 40(6), 1244-1253. doi:10.1093/schbul/sbu033Ben-Zeev, D., Kaiser, S. M., & Krzos, I. (2014). Remote «Hovering» With Individuals With Psychotic Disorders and Substance Use: Feasibility, Engagement, and Therapeutic Alliance With a Text-Messaging Mobile Interventionist. Journal of Dual Diagnosis, 10(4), 197-203. doi:10.1080/15504263.2014.962336Berry, N., Lobban, F., Emsley, R., & Bucci, S. (2016). Acceptability of Interventions Delivered Online and Through Mobile Phones for People Who Experience Severe Mental Health Problems: A Systematic Review. Journal of Medical Internet Research, 18(5), e121. doi:10.2196/jmir.5250Bonet, L., Izquierdo, C., Escartí, M. J., Sancho, J. V., Arce, D., Blanquer, I., & Sanjuan, J. (2017). Utilización de tecnologías móviles en pacientes con psicosis: una revisión sistemática. Revista de Psiquiatría y Salud Mental, 10(3), 168-178. doi:10.1016/j.rpsm.2017.01.003Bonet, L., Llácer, B., Hernandez-Viadel, M., Arce, D., Blanquer, I., Cañete, C., … Sanjuán, J. (2018). Differences in the Use and Opinions About New eHealth Technologies Among Patients With Psychosis: Structured Questionnaire. JMIR Mental Health, 5(3), e51. doi:10.2196/mental.9950Borzekowski, D. L. G., Leith, J., Medoff, D. R., Potts, W., Dixon, L. B., Balis, T., … Himelhoch, S. (2009). Use of the Internet and Other Media for Health Information Among Clinic Outpatients With Serious Mental Illness. Psychiatric Services, 60(9), 1265-1268. doi:10.1176/ps.2009.60.9.1265Brenner, C. J., & Ben-Zeev, D. (2014). Affective forecasting in schizophrenia: Comparing predictions to real-time Ecological Momentary Assessment (EMA) ratings. Psychiatric Rehabilitation Journal, 37(4), 316-320. doi:10.1037/prj0000105Bucci, S., Barrowclough, C., Ainsworth, J., Machin, M., Morris, R., Berry, K., … Haddock, G. (2018). Actissist: Proof-of-Concept Trial of a Theory-Driven Digital Intervention for Psychosis. Schizophrenia Bulletin, 44(5), 1070-1080. doi:10.1093/schbul/sby032Camacho, E., Levin, L., & Torous, J. (2019). Smartphone Apps to Support Coordinated Specialty Care for Prodromal and Early Course Schizophrenia Disorders: Systematic Review. Journal of Medical Internet Research, 21(11), e16393. doi:10.2196/16393Cannon-Spoor, H. E., Potkin, S. G., & Wyatt, R. J. (1982). Measurement of Premorbid Adjustment in Chronic Schizophrenia. Schizophrenia Bulletin, 8(3), 470-484. doi:10.1093/schbul/8.3.470Cresswell, K., & Sheikh, A. (2013). Organizational issues in the implementation and adoption of health information technology innovations: An interpretative review. International Journal of Medical Informatics, 82(5), e73-e86. doi:10.1016/j.ijmedinf.2012.10.007DiFilippo, K. N., Huang, W., & Chapman-Novakofski, K. M. (2017). A New Tool for Nutrition App Quality Evaluation (AQEL): Development, Validation, and Reliability Testing. JMIR mHealth and uHealth, 5(10), e163. doi:10.2196/mhealth.7441Dixon, L. (2017). What It Will Take to Make Coordinated Specialty Care Available to Anyone Experiencing Early Schizophrenia. JAMA Psychiatry, 74(1), 7. doi:10.1001/jamapsychiatry.2016.2665Endicott, J. (1976). The Global Assessment Scale. Archives of General Psychiatry, 33(6), 766. doi:10.1001/archpsyc.1976.01770060086012Firth, J., Cotter, J., Torous, J., Bucci, S., Firth, J. A., & Yung, A. R. (2015). Mobile Phone Ownership and Endorsement of «mHealth» Among People With Psychosis: A Meta-analysis of Cross-sectional Studies. Schizophrenia Bulletin, 42(2), 448-455. doi:10.1093/schbul/sbv132García, S., Martínez-Cengotitabengoa, M., López-Zurbano, S., Zorrilla, I., López, P., Vieta, E., & González-Pinto, A. (2016). Adherence to Antipsychotic Medication in Bipolar Disorder and Schizophrenic Patients. Journal of Clinical Psychopharmacology, 36(4), 355-371. doi:10.1097/jcp.0000000000000523Gay, K., Torous, J., Joseph, A., Pandya, A., & Duckworth, K. (2016). Digital Technology Use Among Individuals with Schizophrenia: Results of an Online Survey. JMIR Mental Health, 3(2), e15. doi:10.2196/mental.5379Gitlow, L., Abdelaal, F., Etienne, A., Hensley, J., Krukowski, E., & Toner, M. (2017). Exploring the Current Usage and Preferences for Everyday Technology among People with Serious Mental Illnesses. Occupational Therapy in Mental Health, 33(1), 1-14. doi:10.1080/0164212x.2016.1211061Granja, C., Janssen, W., & Johansen, M. A. (2018). Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature. Journal of Medical Internet Research, 20(5), e10235. doi:10.2196/10235Hogan, T. P., Awad, A. G., & Eastwood, R. (1983). A self-report scale predictive of drug compliance in schizophrenics: reliability and discriminative validity. Psychological Medicine, 13(1), 177-183. doi:10.1017/s0033291700050182Instituto Nacional de Estadística (INE).2016. Encuesta sobre equipamiento y uso de tecnologías de información y comunicación en los hogares. Available on:http://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176741&menu=ultiDatos&idp=1254735976608. Archived at:http://www.webcitation.org/6μ6YxYOTEKannisto, K. A., Adams, C. E., Koivunen, M., Katajisto, J., & Va lima ki, M. (2015). Feedback on SMS reminders to encourage adherence among patients taking antipsychotic medication: a cross-sectional survey nested within a randomised trial. BMJ Open, 5(11), e008574-e008574. doi:10.1136/bmjopen-2015-008574Kimhy, D., Vakhrusheva, J., Liu, Y., & Wang, Y. (2014). Use of mobile assessment technologies in inpatient psychiatric settings. Asian Journal of Psychiatry, 10, 90-95. doi:10.1016/j.ajp.2014.04.004Lal, S., Dell’Elce, J., Tucci, N., Fuhrer, R., Tamblyn, R., & Malla, A. (2015). Preferences of Young Adults With First-Episode Psychosis for Receiving Specialized Mental Health Services Using Technology: A Survey Study. JMIR Mental Health, 2(2), e18. doi:10.2196/mental.4400Lauckner, C., & Whitten, P. (2015). The State and Sustainability of Telepsychiatry Programs. The Journal of Behavioral Health Services & Research, 43(2), 305-318. doi:10.1007/s11414-015-9461-zMacias, C., Panch, T., Hicks, Y. M., Scolnick, J. S., Weene, D. L., Öngür, D., & Cohen, B. M. (2015). Using Smartphone Apps to Promote Psychiatric and Physical Well-Being. Psychiatric Quarterly, 86(4), 505-519. doi:10.1007/s11126-015-9337-7Miller, B. J., Stewart, A., Schrimsher, J., Peeples, D., & Buckley, P. F. (2015). How connected are people with schizophrenia? Cell phone, computer, email, and social media use. Psychiatry Research, 225(3), 458-463. doi:10.1016/j.psychres.2014.11.067Ministerio de sanidad consumo y bienestar social (MSCBS).2019. Plan de calidad para el Sistema Nacional de salud. Available on:https://www.mscbs.gob.es/organizacion/sns/planCalidadSNS/home.htm. Archived at:http://www.webcitation.org/787eGSHEqMorisky, D. E., Green, L. W., & Levine, D. M. (1986). Concurrent and Predictive Validity of a Self-reported Measure of Medication Adherence. Medical Care, 24(1), 67-74. doi:10.1097/00005650-198601000-00007National Alliance on Mental Illness (NAMI).2014. Health and Technology study. Available on:http://www.nami.org/About‐NAMI/Publications‐Reports/Survey‐Reports/Health‐and‐Technology‐Study‐(2014). Archived at:http://www.webcitation.org/6μ6XgrKXhPalmier-Claus, J. E., Rogers, A., Ainsworth, J., Machin, M., Barrowclough, C., Laverty, L., … Lewis, S. W. (2013). Integrating mobile-phone based assessment for psychosis into people’s everyday lives and clinical care: a qualitative study. BMC Psychiatry, 13(1). doi:10.1186/1471-244x-13-34Robotham, D., Satkunanathan, S., Doughty, L., & Wykes, T. (2016). Do We Still Have a Digital Divide in Mental Health? A Five-Year Survey Follow-up. Journal of Medical Internet Research, 18(11), e309. doi:10.2196/jmir.6511Španiel, F., Vohlídka, P., Kožený, J., Novák, T., Hrdlička, J., Motlová, L., … Höschl, C. (2008). The Information Technology Aided Relapse Prevention Programme in Schizophrenia: an extension of a mirror-design follow-up. International Journal of Clinical Practice, 62(12), 1943-1946. doi:10.1111/j.1742-1241.2008.01903.xStoyanov, S. R., Hides, L., Kavanagh, D. J., & Wilson, H. (2016). Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS). JMIR mHealth and uHealth, 4(2), e72. doi:10.2196/mhealth.5849Torous, J., & Keshavan, M. (2018). A new window into psychosis: The rise digital phenotyping, smartphone assessment, and mobile monitoring. Schizophrenia Research, 197, 67-68. doi:10.1016/j.schres.2018.01.005Trefflich, F., Kalckreuth, S., Mergl, R., & Rummel-Kluge, C. (2015). Psychiatric patients׳ internet use corresponds to the internet use of the general public. Psychiatry Research, 226(1), 136-141. doi:10.1016/j.psychres.2014.12.037Wang, R., Aung, M. S. H., Abdullah, S., Brian, R., Campbell, A. T., Choudhury, T., … Ben-Zeev, D. (2016). CrossCheck. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. doi:10.1145/2971648.2971740Zanaboni, P., Ngangue, P., Mbemba, G. I. C., Schopf, T. R., Bergmo, T. S., & Gagnon, M.-P. (2018). Methods to Evaluate the Effects of Internet-Based Digital Health Interventions for Citizens: Systematic Review of Reviews. Journal of Medical Internet Research, 20(6), e10202. doi:10.2196/1020

    ReMindCare App for Early Psychosis: Pragmatic Real World Intervention and Usability Study

    Get PDF
    [EN] Background: eHealth interventions are widely used in clinical trials and increasingly in care settings as well; however, their efficacy in real-world contexts remains unknown. ReMindCare is a smartphone app that has been systematically implemented in a first episode of psychosis program (FEPP) for patients with early psychosis since 2018. Objective: The objective of this study was to assess the efficacy of ReMindCare after 19 months of use in the clinic and varying use by individual patients. Methods: The integration of the ReMindCare app into the FEPP started in October 2018. Patients with early psychosis self-selected to the app (ReMindCare group) or treatment as usual (TAU group). The outcome variables considered were adherence to the intervention and number of relapses, hospital admissions, and visits to urgent care units. Data from 90 patients with early psychosis were analyzed: 59 in the ReMindCare group and 31 in the TAU group. The mean age of the sample was 32.8 (SD 9.4) years, 73% (66/90) were males, 91% (83/90) were White, and 81% (74/90) were single. Results: Significant differences between the ReMindCare and TAU groups were found in the number of relapses, hospitalizations, and visits to urgent care units, with each showing benefits for the app. Only 20% (12/59) of patients from the ReMindCare group had a relapse, while 58% (18/31) of the TAU patients had one or more relapses (chi(2) =13.7, P=.001). Moreover, ReMindCare patients had fewer visits to urgent care units (chi(2) =7.4, P=.006) and fewer hospitalizations than TAU patients (chi(2) =4.6, P=.03). The mean of days using the app was 352.2 (SD 191.2; min/max: 18-594), and the mean of engagement was 84.5 (SD 16.04). Conclusions: To our knowledge, this is the first eHealth intervention that has preliminarily proven its benefits in the real-world treatment of patients with early psychosis.This study was supported by the Sanitary Research Institute of the University Clinic Hospital and the Mental Health Networking Biomedical Centre. It was also supported by the Generalitat Valenciana and the Program for Scientific Research, Technological Development, and Innovation in the Generalitat Valenciana of the European Union (2017/9830). It was also supported by grants from the Generalitat Valenciana (PROMETEO/2016/082, PROMETEO/2020/024), Carlos III Health Institute (PI13/00447; PI17/00402), and European Union through the European Regional Development Fund.Bonet, L.; Torous, J.; Arce Grilo, AD.; Blanquer Espert, I.; Sanjuan, J. (2020). ReMindCare App for Early Psychosis: Pragmatic Real World Intervention and Usability Study. JMIR mHealth and uHealth. 8(11):1-13. https://doi.org/10.2196/22997S113811Firth, J., Cotter, J., Torous, J., Bucci, S., Firth, J. A., & Yung, A. R. (2015). Mobile Phone Ownership and Endorsement of «mHealth» Among People With Psychosis: A Meta-analysis of Cross-sectional Studies. Schizophrenia Bulletin, 42(2), 448-455. doi:10.1093/schbul/sbv132Bonet, L., Izquierdo, C., Escartí, M. J., Sancho, J. V., Arce, D., Blanquer, I., & Sanjuan, J. (2017). Utilización de tecnologías móviles en pacientes con psicosis: una revisión sistemática. Revista de Psiquiatría y Salud Mental, 10(3), 168-178. doi:10.1016/j.rpsm.2017.01.003Kannarkat, J. T., Smith, N. N., & McLeod-Bryant, S. A. (2020). Mobilization of Telepsychiatry in Response to COVID-19—Moving Toward 21st Century Access to Care. Administration and Policy in Mental Health and Mental Health Services Research, 47(4), 489-491. doi:10.1007/s10488-020-01044-zTorous, J., & Keshavan, M. (2020). COVID-19, mobile health and serious mental illness. Schizophrenia Research, 218, 36-37. doi:10.1016/j.schres.2020.04.013Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., McIntyre, R. S., … Ho, C. (2020). A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain, Behavior, and Immunity, 87, 40-48. doi:10.1016/j.bbi.2020.04.028Trefflich, F., Kalckreuth, S., Mergl, R., & Rummel-Kluge, C. (2015). Psychiatric patients׳ internet use corresponds to the internet use of the general public. Psychiatry Research, 226(1), 136-141. doi:10.1016/j.psychres.2014.12.037Gay, K., Torous, J., Joseph, A., Pandya, A., & Duckworth, K. (2016). Digital Technology Use Among Individuals with Schizophrenia: Results of an Online Survey. JMIR Mental Health, 3(2), e15. doi:10.2196/mental.5379Bonet, L., Llácer, B., Hernandez-Viadel, M., Arce, D., Blanquer, I., Cañete, C., … Sanjuán, J. (2018). Differences in the Use and Opinions About New eHealth Technologies Among Patients With Psychosis: Structured Questionnaire. JMIR Mental Health, 5(3), e51. doi:10.2196/mental.9950Hau, Y. S., Kim, J. K., Hur, J., & Chang, M. C. (2020). How about actively using telemedicine during the COVID-19 pandemic? Journal of Medical Systems, 44(6). doi:10.1007/s10916-020-01580-zBucci, S., Berry, N., Morris, R., Berry, K., Haddock, G., Lewis, S., & Edge, D. (2019). «They Are Not Hard-to-Reach Clients. We Have Just Got Hard-to-Reach Services.» Staff Views of Digital Health Tools in Specialist Mental Health Services. Frontiers in Psychiatry, 10. doi:10.3389/fpsyt.2019.00344Arango, C., Bernardo, M., Bonet, P., Cabrera, A., Crespo-Facorro, B., Cuesta, M. J., … Melau, M. (2017). Cuando la asistencia no sigue a la evidencia: el caso de la falta de programas de intervención temprana en psicosis en España. Revista de Psiquiatría y Salud Mental, 10(2), 78-86. doi:10.1016/j.rpsm.2017.01.001Camacho, E., Levin, L., & Torous, J. (2019). Smartphone Apps to Support Coordinated Specialty Care for Prodromal and Early Course Schizophrenia Disorders: Systematic Review. Journal of Medical Internet Research, 21(11), e16393. doi:10.2196/16393Correll, C. U., Galling, B., Pawar, A., Krivko, A., Bonetto, C., Ruggeri, M., … Kane, J. M. (2018). Comparison of Early Intervention Services vs Treatment as Usual for Early-Phase Psychosis. JAMA Psychiatry, 75(6), 555. doi:10.1001/jamapsychiatry.2018.0623Bucci, S., Barrowclough, C., Ainsworth, J., Machin, M., Morris, R., Berry, K., … Haddock, G. (2018). Actissist: Proof-of-Concept Trial of a Theory-Driven Digital Intervention for Psychosis. Schizophrenia Bulletin, 44(5), 1070-1080. doi:10.1093/schbul/sby032Eisner, E., Drake, R. J., Berry, N., Barrowclough, C., Emsley, R., Machin, M., & Bucci, S. (2019). Development and Long-Term Acceptability of ExPRESS, a Mobile Phone App to Monitor Basic Symptoms and Early Signs of Psychosis Relapse. JMIR mHealth and uHealth, 7(3), e11568. doi:10.2196/11568Ben-Zeev, D., Brian, R., Wang, R., Wang, W., Campbell, A. T., Aung, M. S. H., … Scherer, E. A. (2017). CrossCheck: Integrating self-report, behavioral sensing, and smartphone use to identify digital indicators of psychotic relapse. Psychiatric Rehabilitation Journal, 40(3), 266-275. doi:10.1037/prj0000243Torous, J., Woodyatt, J., Keshavan, M., & Tully, L. M. (2019). A new hope for early psychosis care: the evolving landscape of digital care tools. The British Journal of Psychiatry, 214(5), 269-272. doi:10.1192/bjp.2019.8Torous, J., Lipschitz, J., Ng, M., & Firth, J. (2020). Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. Journal of Affective Disorders, 263, 413-419. doi:10.1016/j.jad.2019.11.167Killikelly, C., He, Z., Reeder, C., & Wykes, T. (2017). Improving Adherence to Web-Based and Mobile Technologies for People With Psychosis: Systematic Review of New Potential Predictors of Adherence. JMIR mHealth and uHealth, 5(7), e94. doi:10.2196/mhealth.7088Krzystanek, M., Krysta, K., & Skałacka, K. (2017). Treatment Compliance in the Long-Term Paranoid Schizophrenia Telemedicine Study. Journal of Technology in Behavioral Science, 2(2), 84-87. doi:10.1007/s41347-017-0016-4Arnold, C., Villagonzalo, K.-A., Meyer, D., Farhall, J., Foley, F., Kyrios, M., & Thomas, N. (2019). Predicting engagement with an online psychosocial intervention for psychosis: Exploring individual- and intervention-level predictors. Internet Interventions, 18, 100266. doi:10.1016/j.invent.2019.100266Ross, J., Stevenson, F., Lau, R., & Murray, E. (2016). Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update). Implementation Science, 11(1). doi:10.1186/s13012-016-0510-7Allan, S., Bradstreet, S., Mcleod, H., Farhall, J., Lambrou, M., … Gleeson, J. (2019). Developing a Hypothetical Implementation Framework of Expectations for Monitoring Early Signs of Psychosis Relapse Using a Mobile App: Qualitative Study. Journal of Medical Internet Research, 21(10), e14366. doi:10.2196/14366Palmier-Claus, J. E., Rogers, A., Ainsworth, J., Machin, M., Barrowclough, C., Laverty, L., … Lewis, S. W. (2013). Integrating mobile-phone based assessment for psychosis into people’s everyday lives and clinical care: a qualitative study. BMC Psychiatry, 13(1). doi:10.1186/1471-244x-13-34Kannisto, K. A., Adams, C. E., Koivunen, M., Katajisto, J., & Va lima ki, M. (2015). Feedback on SMS reminders to encourage adherence among patients taking antipsychotic medication: a cross-sectional survey nested within a randomised trial. BMJ Open, 5(11), e008574-e008574. doi:10.1136/bmjopen-2015-008574Torous, J. B. (2018). Focusing on the Future of Mobile Mental Health and Smartphone Interventions. Psychiatric Services, 69(9), 945-945. doi:10.1176/appi.ps.201800308Bonet, L., Torous, J., Arce, D., Blanquer, I., & Sanjuán, J. (2020). ReMindCare , an app for daily clinical practice in patients with first episode psychosis: A pragmatic real‐world study protocol. Early Intervention in Psychiatry, 15(1), 183-192. doi:10.1111/eip.12960Endicott, J. (1976). The Global Assessment Scale. Archives of General Psychiatry, 33(6), 766. doi:10.1001/archpsyc.1976.01770060086012Cannon-Spoor, H. E., Potkin, S. G., & Wyatt, R. J. (1982). Measurement of Premorbid Adjustment in Chronic Schizophrenia. Schizophrenia Bulletin, 8(3), 470-484. doi:10.1093/schbul/8.3.470Greer, B., Robotham, D., Simblett, S., Curtis, H., Griffiths, H., & Wykes, T. (2019). Digital Exclusion Among Mental Health Service Users: Qualitative Investigation. Journal of Medical Internet Research, 21(1), e11696. doi:10.2196/11696Rus-Calafell, M., & Schneider, S. (2020). Are we there yet?!—a literature review of recent digital technology advances for the treatment of early psychosis. mHealth, 6, 3-3. doi:10.21037/mhealth.2019.09.14Choi, K. R., Heilemann, M. V., Fauer, A., & Mead, M. (2020). A Second Pandemic: Mental Health Spillover From the Novel Coronavirus (COVID-19). Journal of the American Psychiatric Nurses Association, 26(4), 340-343. doi:10.1177/107839032091980

    SETD7 regulates the differentiation of human embryonic stem cells

    Get PDF
    The successful use of specialized cells in regenerative medicine requires an optimization in the differentiation protocols that are currently used. Understanding the molecular events that take place during the differentiation of human pluripotent cells is essential for the improvement of these protocols and the generation of high quality differentiated cells. In an effort to understand the molecular mechanisms that govern differentiation we identify the methyltransferase SETD7 as highly induced during the differentiation of human embryonic stem cells and differentially expressed between induced pluripotent cells and somatic cells. Knock-down of SETD7 causes differentiation defects in human embryonic stem cell including delay in both the silencing of pluripotency-related genes and the induction of differentiation genes. We show that SETD7 methylates linker histone H1 in vitro causing conformational changes in H1. These effects correlate with a decrease in the recruitment of H1 to the pluripotency genes OCT4 and NANOG during differentiation in the SETD7 knockdown that might affect the proper silencing of these genes during differentiation.M.J.B. was partially supported by the Ramón y Cajal program of MEC (RYC-2007-01510). B.S. was a recipient of a predoctoral fellowship from MEC (BES-2008-009567). C.M. was supported by PT13/0001/0041 PRB2-ISCIII-SGEFI- FEDER-PE I+D+i 2013-2016. J.C. was partially supported by Fundación CELLEX. This work was partially supported by grant RD12/0019/0034 TERCEL-RETICS-ISCIII-MINECO-FEDER, grant SAF2009-08588 from MICINN to M.J.B and grant BFU2014-52237 to A.J.Peer Reviewe

    Utilización de tecnologías móviles en pacientes con psicosis: una revisión sistemática.

    Full text link
    [EN] There is a growing interest in mobile Health interventions (m-Health) in patients with psychosis. The aim of this study is to conduct a systematic review in order to analysethe current state of research in this area. The search of articles was carried out following the PRISMA criteria, focusing on those studies that used mobile technologies in patients with psychosis during the period from 1990 to 2016. A total of 20 articles were selected from the 431 studies found. Three types of studies are distinguished: 1) Analysis of quality and usability, 2) Improving treatment adherence and reducing hospital admissions, and 3) Analysisof patient symptoms. CONCLUSIONS: m-Health interventions are feasible, and are easy to use for patients with psychosis. They evaluate the evolution of psychotic symptoms more efficiently, and improve adherence to treatment, as well as symptoms and hospital admissions. However, a particular strategy does not stand out over the rest, because differences in methodology make them difficult to compare.[ES] Introducción: Hay un creciente interés en las intervenciones mobile Health (m-Health) en pacientes con psicosis. El objetivo de este estudio es realizar una revisión sistemática para analizar el estado actual de la investigación en este ámbito. Metodología: Búsqueda en las bases de datos PsycINFO, PubMED, SCOPUS, Medline, ISI Web of Knowledge e IME del CSIC. Intervenciones con tecnologías móviles en pacientes con psicosis. Resultados: De un total de 431 artículos se seleccionaron 20. Se diferencian tres tipos de intervenciones: (1) Análisis de calidad y usabilidad, (2) Mejora de la adherencia, síntomas y reducción de hospitalizaciones, (3) Análisis de la sintomatología del paciente. Conclusiones: Las intervenciones m-Health son viables y resultan fáciles de utilizar para los pacientes con psicosis. Evalúan de forma más eficiente la evolución de los síntomas psicóticos y mejoran la adherencia al tratamiento, síntomas y hospitalizaciones. No se puede destacar una estrategia sobre las demás debido a que las diferencias en la metodología las hace difícilmente comparables.A ‘‘Prometeo’’ support grant from the Conselleria de Sanidad de la Comunidad Valenciana.Bonet, L.; Izquierdo, C.; Escartí, MJ.; Sancho, JV.; Arce Grilo, AD.; Blanquer Espert, I.; Sanjuan Arias, J. (2017). Use of mobile technologies in patients with psychosis: A systematic review. Revista de Psiquiatría y Salud Mental. 10(3):168-178. doi:10.1016/j.rpsm.2017.01.003S16817810
    corecore