Suchergebnisse

The SEYLE project was funded by the European Union Seventh Framework Program (FP7; HEALTH-F2-2009-223091). Judit Balazs was supported by the Ja´nos Bolyai Research Scholarship of the Hungarian Academy of Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Gambadauro, P., Carli, V., Hadlaczky, G., Sarchiapone, M., Apter, A., Balazs, J., Banzer, R., Bobes, J., Brunner, R., Cosman, D., Farkas, L., Haring, C., Hoven, C.W., Kaess, M., Kahn, J.P., McMahon, E., Postuvan, V., Sisask, M., Värnik, A., Sedivy, N.Z., Wasserman, D.

Abstract. Background: Since the mid-1990s concerns have been raised regarding the possible links between suicide and the Internet, especially among adolescents and young adults. Aims: To identify the nature and extent of the scientific publications, especially original research studies, on suicide and the Internet, and to investigate how the field has developed over time. In particular, this mapping study looks at types of publications, topic areas, focus of original research papers, and suicide-related variables of interest in publications. Method: A search of three major databases (PubMED, PsycINFO, and Sociological Abstracts) was conducted to identify papers published until the end of January 2015. Results: The study identified 237 publications on suicide and the Internet published from 1997 to the end of January 2015. These included 122 original research papers. The three most frequent topic areas covered in publications were searching for information on suicide, online interventions, and online suicide-related behaviors. The online mediums most frequently studied were online forums/message boards, search engines, intervention and information websites, and social media. Limitations: The mapping study did not include an analysis of results of research studies and did not assess their quality. Conclusion: The field is rapidly evolving, as seen in the recent increase in the number of publications. However, there are gaps in terms of the countries where research is conducted and the coverage of topics.

Abstract. Background: Self-injurious behaviors in adolescence are a serious public health concern. Aims: The current study aims to expand our understanding of motives for direct self-injurious behaviors (D-SIB). We examined the explicit motives but also the actual antecedents and consequences of D-SIB over time. Method: As part of the Saving and Empowering Young Lives in Europe (SEYLE) study, adolescents between the ages of 14 and 18 years from Israel completed self-report questionnaires at baseline, 3-month, and 12-month follow-ups. Results: Decreases in social support predicted later increases in D-SIB, an effect mediated by negative affect. Both peer and parental support also exerted quadratic effects on D-SIB. Thus, low as well as high support predicted subsequent D-SIB. In turn, D-SIB was followed by increased peer and parental support. Limitations: Our methodology relies on self-reports, affected by social desirability and recall biases. Conclusion: The findings support a causal path for the development of D-SIB: from interpersonal distress to emotional distress and then to D-SIB. They also point to interesting avenues regarding subgroupings of adolescents who self-injure depending on their motives. Finally, our results reveal that D-SIB, although of negative import, might paradoxically be effective in serving certain functions such as gaining support from parents and peers.

Risk assessment of suicidal behavior is a time-consuming but notoriously inaccurate activity formental health services globally. In the last 50 years a large number of tools have been designed for suicide risk assessment, and tested in a wide variety of populations, but studies show that these tools suffer fromlow positive predictive values.More recently, advances in research fields such as machine learning and natural language processing applied on large datasets have shown promising results for health care, and may enable an important shift in advancing precision medicine. In this conceptual review, we discuss established risk assessment tools and examples of novel data-driven approaches that have been used for identification of suicidal behavior and risk. We provide a perspective on the strengths and weaknesses of these applications to mental health-related data, and suggest research directions to enable improvement in clinical practice ; This manuscript was written as a result of a workshop that was held at the Institute of Psychiatry, Psychology and Neuroscience, King's College London, financially supported by the European Science Foundation (ESF) Research Networking Programme Evaluating Information Access Systems: http://elias-network.eu/. SV is supported by the Swedish Research Council (2015-00359) and the Marie Skłodowska Curie Actions, Cofund, Project INCA 600398. EB-G is partially supported by grants from Instituto de Salud Carlos III (ISCIII PI13/02200; PI16/01852), Delegación del Gobierno para el Plan Nacional de Drogas (20151073); American Foundation for Suicide Prevention (AFSP) (LSRG- 1-005-16). NW is supported by the UCLH NIHR Biomedical Research Centre. DN is supported by The Alan Turing Institute under the EPSRC grant EP/N510129/1, with an Alan Turing Institute Fellowship (TU/A/000006). RP has received support from a Medical Research Council (MRC) Health Data Research UK Fellowship (MR/S003118/1) and a Starter Grant for Clinical Lecturers (SGL015/1020) supported by the Academy of Medical Sciences, The Wellcome Trust, MRC, British Heart Foundation, Arthritis Research UK, the Royal College of Physicians and Diabetes UK. DL is supported by the UK Medical Research Council under grant MR/N028244/2 and the King's Centre for Military Health Research. JD is supported by a Medical Research Council (MRC) Clinical Research Training Fellowship (MR/L017105/1). RD is funded by a Clinician Scientist Fellowship (research project e-HOST-IT) from the Health Foundation in partnership with the Academy of Medical Sciences

BACKGROUND: This study assessed the effectiveness of the NEVERMIND e-health system, consisting of a smart shirt and a mobile application with lifestyle behavioural advice, mindfulness-based therapy, and cognitive behavioural therapy, in reducing depressive symptoms among patients diagnosed with severe somatic conditions. Our hypothesis was that the system would significantly decrease the level of depressive symptoms in the intervention group compared to the control group. METHODS: This pragmatic, randomised controlled trial included 425 patients diagnosed with myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants were recruited from hospitals in Turin and Pisa (Italy), and Lisbon (Portugal), and were randomly assigned to either the NEVERMIND intervention or to the control group. Clinical interviews and structured questionnaires were administered at baseline, 12 weeks, and 24 weeks. The primary outcome was depressive symptoms at 12 weeks measured by the Beck Depression Inventory II (BDI-II). Intention-to-treat analyses included 425 participants, while the per-protocol analyses included 333 participants. This trial is registered in the German Clinical Trials Register, DRKS00013391. FINDINGS: Patients were recruited between Dec 4, 2017, and Dec 31, 2019, with 213 assigned to the intervention and 212 to the control group. The sample had a mean age of 59·41 years (SD=10·70), with 44·24% women. Those who used the NEVERMIND system had statistically significant lower depressive symptoms at the 12-week follow-up (mean difference=-3·03, p<0·001; 95% CI -4·45 to -1·62) compared with controls, with a clinically relevant effect size (Cohen's d=0·39). INTERPRETATION: The results of this study show that the NEVERMIND system is superior to standard care in reducing and preventing depressive symptoms among patients with the studied somatic conditions. FUNDING: The NEVERMIND project received funding from the European Union's Horizon 2020 Research and Innovation Programme ...

Background This study assessed the effectiveness of the NEVERMIND e-health system, consisting of a smart shirt and a mobile application with lifestyle behavioural advice, mindfulness-based therapy, and cognitive behavioural therapy, in reducing depressive symptoms among patients diagnosed with severe somatic conditions. Our hypothesis was that the system would significantly decrease the level of depressive symptoms in the intervention group compared to the control group. Methods This pragmatic, randomised controlled trial included 425 patients diagnosed with myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants were recruited from hospitals in Turin and Pisa (Italy), and Lisbon (Portugal), and were randomly assigned to either the NEVERMIND intervention or to the control group. Clinical interviews and structured questionnaires were administered at baseline, 12 weeks, and 24 weeks. The primary outcome was depressive symptoms at 12 weeks measured by the Beck Depression Inventory II (BDI-II). Intention-to-treat analyses included 425 participants, while the per-protocol analyses included 333 participants. This trial is registered in the German Clinical Trials Register, DRKS00013391. Findings Patients were recruited between Dec 4, 2017, and Dec 31, 2019, with 213 assigned to the intervention and 212 to the control group. The sample had a mean age of 59·41 years (SD=10·70), with 44·24% women. Those who used the NEVERMIND system had statistically significant lower depressive symptoms at the 12-week follow-up (mean difference=-3·03, p<0·001; 95% CI -4·45 to -1·62) compared with controls, with a clinically relevant effect size (Cohen's d=0·39). Interpretation The results of this study show that the NEVERMIND system is superior to standard care in reducing and preventing depressive symptoms among patients with the studied somatic conditions. Funding The NEVERMIND project received funding from the European Union's Horizon 2020 Research and Innovation Programme under ...