#Internet #addiction #antecendants: #Self-control as a predictor
Authors: #Mohammad_Sadegh_Shirinkam, #Amir_Mohammad_Shahsavarani, #Leila_Moayer_Toroghi, #Mahdiye_Mahmoodabadi, #Alireza_Mohammadi and #Kolsum_Sattari
Abstract
#Internet_addiction is a result of #penetration of internet #technology to the #modern #world and has inundated a substantial proportion of #human #societies, so that many of mental professionals have considered it as a mounting threatening issue of mental health. Many factors are suggested to be of capability of #predicting internet addiction, include #self_efficacy and #self_control, whose roles are evaluated in this study. This survey study was conducted on 395 female and male #university #students of SardarJangal University, Rasht, Iran. #Instruments comprised #Internet #Addiction #Test , and Self-Control Scale (Tangney, 2004), which were administered by all participants. findings of #regression analysis showed that self-control has #significant negative relation with internet addiction (p<.05) and male students gained higher scores in internet addiction than females. Moreover, no significant difference was found among students of different university majors in internet addiction scores. It appears that self-control abilities can reduce the rate of internet addiction in university students. Therefore, future programs and plans of tri-layer #prevention can focus on teaching for self-control among university students as well as school-ageed students and families to deliberately decrease internet addiction in various sectors of society.
Keywords: #Internet_addiction, #self_control, #internet_addiction_disorder (#IAD), #Problematic_internet_use (#PIU),
#internet_addiction_prevention, #university_students.
http://ijmrhs.com/internet-addiction-antecendants-self-control-as-a-predictor/
Authors: #Mohammad_Sadegh_Shirinkam, #Amir_Mohammad_Shahsavarani, #Leila_Moayer_Toroghi, #Mahdiye_Mahmoodabadi, #Alireza_Mohammadi and #Kolsum_Sattari
Abstract
#Internet_addiction is a result of #penetration of internet #technology to the #modern #world and has inundated a substantial proportion of #human #societies, so that many of mental professionals have considered it as a mounting threatening issue of mental health. Many factors are suggested to be of capability of #predicting internet addiction, include #self_efficacy and #self_control, whose roles are evaluated in this study. This survey study was conducted on 395 female and male #university #students of SardarJangal University, Rasht, Iran. #Instruments comprised #Internet #Addiction #Test , and Self-Control Scale (Tangney, 2004), which were administered by all participants. findings of #regression analysis showed that self-control has #significant negative relation with internet addiction (p<.05) and male students gained higher scores in internet addiction than females. Moreover, no significant difference was found among students of different university majors in internet addiction scores. It appears that self-control abilities can reduce the rate of internet addiction in university students. Therefore, future programs and plans of tri-layer #prevention can focus on teaching for self-control among university students as well as school-ageed students and families to deliberately decrease internet addiction in various sectors of society.
Keywords: #Internet_addiction, #self_control, #internet_addiction_disorder (#IAD), #Problematic_internet_use (#PIU),
#internet_addiction_prevention, #university_students.
http://ijmrhs.com/internet-addiction-antecendants-self-control-as-a-predictor/
روشی جدید برای #تشخیص #پاسخدهی #مبتلایان به #اختلال #دوقطبی (#BD) به #لیتیوم
#Neurons #derived from #patients with bipolar disorder divide into intrinsically different sub-populations of neurons, #predicting the patients’ #responsiveness to #lithium
🔍🖌پژوهشگران انستیتو #سالک در لاجولا کالیفرنیا 🇺🇸 به تازگی روشی ابداع نموده اند که بر اساس آن می توان با دقتی بیش از 92% پاسخدهی مبتلایان به اختلال دوقطبی (BD) را به داروی #کربنات #لیتیوم (#اسکالیت) مشخص ساخت؛ ذکر این نکته مهم است که تنها 30% مبتلایان به BD به ترکیبات لیتیوم پاسخ می دهند. فقط در ایالات متحده امریکا بیش از 5 میلیون نفر مبتلا به BD هستند.
🔬پژوهش های پیشین این پژوهشگران مشخص ساخته بود در افراد دارای BD #نورون های #شکنج دندانه ای #هیپوکامپ نسبت به افراد غیر بیمارِ عادی تحریک پذیرترند. در گام بعدی پژوهشگران نوع و الگوهای تحریک پذیری عصبی این افراد و نیز پاسخدهی آنها به لیتیوم را مشخص ساختند. بر پایه نتایج پژوهش فعلی تنها با بررسی سلول های #لمفوسیت B می توان پاسخ دهی افراد به لیتیوم را مشخص ساخت.
Abstract
#Bipolar disorder (#BD) is a #progressive #psychiatric disorder with more than 3% #prevalence worldwide. Affected individuals experience recurrent episodes of #depression and #mania, disrupting normal life and increasing the risk of suicide greatly. The complexity and #genetic #heterogeneity of psychiatric disorders have challenged the development of animal and cellular models. We recently reported that #hippocampal #dentate #gyrus (#DG) #neurons differentiated from induced pluripotent stem cell (#iPSC)-derived #fibroblasts of BD patients are electrophysiologically hyperexcitable. Here we used iPSCs derived from #Epstein–Barr #virus-immortalized #B_lymphocytes to verify that the hyperexcitability of #DG-like neurons is reproduced in this different cohort of patients and #cells. #Lymphocytes are readily available for research with a large number of banked lines with associated patient clinical description. We used whole-cell patch-clamp recordings of over 460 neurons to characterize neurons derived from control individuals and BD patients. #Extensive #functional #analysis showed that intrinsic cell parameters are very different between the two groups of BD neurons, those derived from #lithium (Li)-responsive (LR) #patients and those derived from Li-non-responsive (NR) patients, which led us to partition our BD neurons into two sub-populations of cells and suggested two different #subdisorders. Training a #Naïve #Bayes #classifier with the #electrophysiological features of patients whose responses to Li are known allows for accurate classification with more than 92% success rate for a new patient whose response to Li is unknown. Despite their very different functional profiles, both populations of neurons share a large, #fast #after-hyperpolarization (#AHP). We therefore suggest that the large, fast AHP is a key feature of BD and a main contributor to the fast, #sustained #spiking abilities of BD neurons. Confirming our previous report with fibroblast-derived DG neurons, chronic Li treatment reduced the hyperexcitability in the lymphoblast-derived LR group but not in the NR group, strengthening the validity and utility of this new human cellular model of BD.
لینک منبع 👇🏻(further reading)👇🏻
http://www.nature.com/mp/journal/vaop/ncurrent/full/mp2016260a.html
✅(در صورت جذابیت و علاقمندی به موضوع، مطلب را برای دیگران نیز بازنشر فرمایید).
📢کانال #دکترامیرمحمدشهسوارانی
🍃🌹🌸💐🌸🌹🍃
@DrAmirMohammadShahsavarani
#Neurons #derived from #patients with bipolar disorder divide into intrinsically different sub-populations of neurons, #predicting the patients’ #responsiveness to #lithium
🔍🖌پژوهشگران انستیتو #سالک در لاجولا کالیفرنیا 🇺🇸 به تازگی روشی ابداع نموده اند که بر اساس آن می توان با دقتی بیش از 92% پاسخدهی مبتلایان به اختلال دوقطبی (BD) را به داروی #کربنات #لیتیوم (#اسکالیت) مشخص ساخت؛ ذکر این نکته مهم است که تنها 30% مبتلایان به BD به ترکیبات لیتیوم پاسخ می دهند. فقط در ایالات متحده امریکا بیش از 5 میلیون نفر مبتلا به BD هستند.
🔬پژوهش های پیشین این پژوهشگران مشخص ساخته بود در افراد دارای BD #نورون های #شکنج دندانه ای #هیپوکامپ نسبت به افراد غیر بیمارِ عادی تحریک پذیرترند. در گام بعدی پژوهشگران نوع و الگوهای تحریک پذیری عصبی این افراد و نیز پاسخدهی آنها به لیتیوم را مشخص ساختند. بر پایه نتایج پژوهش فعلی تنها با بررسی سلول های #لمفوسیت B می توان پاسخ دهی افراد به لیتیوم را مشخص ساخت.
Abstract
#Bipolar disorder (#BD) is a #progressive #psychiatric disorder with more than 3% #prevalence worldwide. Affected individuals experience recurrent episodes of #depression and #mania, disrupting normal life and increasing the risk of suicide greatly. The complexity and #genetic #heterogeneity of psychiatric disorders have challenged the development of animal and cellular models. We recently reported that #hippocampal #dentate #gyrus (#DG) #neurons differentiated from induced pluripotent stem cell (#iPSC)-derived #fibroblasts of BD patients are electrophysiologically hyperexcitable. Here we used iPSCs derived from #Epstein–Barr #virus-immortalized #B_lymphocytes to verify that the hyperexcitability of #DG-like neurons is reproduced in this different cohort of patients and #cells. #Lymphocytes are readily available for research with a large number of banked lines with associated patient clinical description. We used whole-cell patch-clamp recordings of over 460 neurons to characterize neurons derived from control individuals and BD patients. #Extensive #functional #analysis showed that intrinsic cell parameters are very different between the two groups of BD neurons, those derived from #lithium (Li)-responsive (LR) #patients and those derived from Li-non-responsive (NR) patients, which led us to partition our BD neurons into two sub-populations of cells and suggested two different #subdisorders. Training a #Naïve #Bayes #classifier with the #electrophysiological features of patients whose responses to Li are known allows for accurate classification with more than 92% success rate for a new patient whose response to Li is unknown. Despite their very different functional profiles, both populations of neurons share a large, #fast #after-hyperpolarization (#AHP). We therefore suggest that the large, fast AHP is a key feature of BD and a main contributor to the fast, #sustained #spiking abilities of BD neurons. Confirming our previous report with fibroblast-derived DG neurons, chronic Li treatment reduced the hyperexcitability in the lymphoblast-derived LR group but not in the NR group, strengthening the validity and utility of this new human cellular model of BD.
لینک منبع 👇🏻(further reading)👇🏻
http://www.nature.com/mp/journal/vaop/ncurrent/full/mp2016260a.html
✅(در صورت جذابیت و علاقمندی به موضوع، مطلب را برای دیگران نیز بازنشر فرمایید).
📢کانال #دکترامیرمحمدشهسوارانی
🍃🌹🌸💐🌸🌹🍃
@DrAmirMohammadShahsavarani
♻️روشی جدید برای تشخیص #طول #عمر
#Precision #Radiology: #Predicting #longevity using feature #engineering and #deep #learning methods in a #radiomics framework
پژوهشگران دانشگاه آدلاید، دانشگاه کوینزلند، و انستیتو تکنیک های پیشرفته لیسبون در پژوهشی که به تازگی منتشر شده است، دریافتند سیستم های هوش مصنوعی قادرتند طول عمر افراد را با مرور #CTاسکن های #اندام های آنان پیش بینی کنند.
در این پژوهش که بر CTاسکن #سینه 48 بیمار صورت گرفت، سیستم های #هوش #مصنوعی (#AI) بر اساس #الگوریتم های #یادگیری #عمیق توانستند با 69 درصد دقت (همانند پیش بینی های معمول پزشکان) احتمال #مرگ #بیمار را در 5 سال آتی پیش بینی کنند. پژوهشگران نتوانستند مشخص کنند که برنامه های هوش مصنوعی دقیقاً بر اساس بررسی کدام بخش از تصاویر CTاسکن پیش بینی را صورت داده اند، اما پیش بینی ها در بیماری های وخیم مزمن (همچون #آمفیزم و بیماری های #قلبی) دقیق تر بود.
Abstract
#Precision #medicine approaches rely on obtaining precise knowledge of the true state of #health of an individual patient, which results from a combination of their #genetic risks and #environmental exposures. This approach is currently limited by the lack of effective and efficient non-invasive medical tests to define the full range of #phenotypic variation associated with individual #health. Such knowledge is critical for improved early intervention, for better #treatment #decisions, and for ameliorating the steadily worsening epidemic of chronic disease. We present proof-of-concept experiments to demonstrate how routinely acquired #cross-sectional #CT #imaging may be used to predict patient #longevity as a proxy for overall individual health and disease status using #computer image analysis techniques. Despite the limitations of a modest dataset and the use of off-the-shelf machine learning methods, our results are comparable to previous ‘manual’ clinical methods for longevity prediction. This work demonstrates that #radiomics techniques can be used to extract #biomarkers relevant to one of the most widely used outcomes in #epidemiological and #clinical research – #mortality, and that #deep #learning with convolutional #neural #networks can be usefully applied to radiomics research. Computer image analysis applied to routinely collected medical images offers substantial potential to enhance #precision #medicine initiatives.
لینک منبع 👇🏻(further reading)👇🏻
https://www.nature.com/articles/s41598-017-01931-w
📢کانال #دکترامیرمحمدشهسوارانی
🍃🌹🌸💐🌸🌹🍃
@DrAmirMohammadShahsavarani
#Precision #Radiology: #Predicting #longevity using feature #engineering and #deep #learning methods in a #radiomics framework
پژوهشگران دانشگاه آدلاید، دانشگاه کوینزلند، و انستیتو تکنیک های پیشرفته لیسبون در پژوهشی که به تازگی منتشر شده است، دریافتند سیستم های هوش مصنوعی قادرتند طول عمر افراد را با مرور #CTاسکن های #اندام های آنان پیش بینی کنند.
در این پژوهش که بر CTاسکن #سینه 48 بیمار صورت گرفت، سیستم های #هوش #مصنوعی (#AI) بر اساس #الگوریتم های #یادگیری #عمیق توانستند با 69 درصد دقت (همانند پیش بینی های معمول پزشکان) احتمال #مرگ #بیمار را در 5 سال آتی پیش بینی کنند. پژوهشگران نتوانستند مشخص کنند که برنامه های هوش مصنوعی دقیقاً بر اساس بررسی کدام بخش از تصاویر CTاسکن پیش بینی را صورت داده اند، اما پیش بینی ها در بیماری های وخیم مزمن (همچون #آمفیزم و بیماری های #قلبی) دقیق تر بود.
Abstract
#Precision #medicine approaches rely on obtaining precise knowledge of the true state of #health of an individual patient, which results from a combination of their #genetic risks and #environmental exposures. This approach is currently limited by the lack of effective and efficient non-invasive medical tests to define the full range of #phenotypic variation associated with individual #health. Such knowledge is critical for improved early intervention, for better #treatment #decisions, and for ameliorating the steadily worsening epidemic of chronic disease. We present proof-of-concept experiments to demonstrate how routinely acquired #cross-sectional #CT #imaging may be used to predict patient #longevity as a proxy for overall individual health and disease status using #computer image analysis techniques. Despite the limitations of a modest dataset and the use of off-the-shelf machine learning methods, our results are comparable to previous ‘manual’ clinical methods for longevity prediction. This work demonstrates that #radiomics techniques can be used to extract #biomarkers relevant to one of the most widely used outcomes in #epidemiological and #clinical research – #mortality, and that #deep #learning with convolutional #neural #networks can be usefully applied to radiomics research. Computer image analysis applied to routinely collected medical images offers substantial potential to enhance #precision #medicine initiatives.
لینک منبع 👇🏻(further reading)👇🏻
https://www.nature.com/articles/s41598-017-01931-w
📢کانال #دکترامیرمحمدشهسوارانی
🍃🌹🌸💐🌸🌹🍃
@DrAmirMohammadShahsavarani
Nature
Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework
Scientific Reports - Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework
♻️#رفتارهای #آتیستیک منجر به افزایش احتمال #خودکشی می شوند.
Are #autistic #traits associated with #suicidality? A test of the #interpersonal-psychological
theory of #suicide in a #non-clinical #young adult sample
پژوهشگران روانشناسی دانشگاه کاونتری و دانشگاه بیرمنگام 🇬🇧، در تحقیقی که نتایج آن نیز به مراجع رسمی ایالات متحده 🇺🇸 و اتحادیه اروپا 🇪🇺 ارائه شده است، دریافتند افرادی که #رگه های #طیف #درخودماندگی (#ASD، #مشکلات #تعاملی و #ارتباطات #اجتماعی) دارند اما مشمول تشخیص این اختلالات نمی شوند در معرض خطر بالای خودکشی هستند.
🔬در این پژوهش که بصورت #آنلاین از 163 نفر بین 18 تا 30 ساله داوطلب به عمل آمد، شاخص های #فرسودگی، #افسردگی، #رگه های #آتیزم، #گرایش به #خودکشی، و #ارتباطات بین فردی مورد سنجش قرار گرفتند.
📚نتایج نشان دادند رگه های رفتارهای درخودمانده از طریق حساسات مورد #ظلم قرار گرفتن و #یاس/#ناامیدی منجر به افزایش چشمگیر رفتارهای خودکشی در جوانان می شوند.
Abstract
#Autism #spectrum #conditions (#ASC) has recently been associated with increased risk of #suicidality. However, no studies have explored how autistic traits may interact with current models of #suicidal #behavior in a #non-clinical #population. The current study therefore explored how #self-reported autistic traits interact with perceived #burdensomeness and #thwarted #belongingness in #predicting #suicidal behavior, in the context of the #Interpersonal-Psychological Theory of Suicide (#IPTS). 163 #young #adults (aged 18–30 years) completed an online #survey including measures of thwarted belonging and perceived burdensomeness (#Interpersonal #Needs #Questionnaire), self-reported autistic traits (#Autism #Spectrum #Quotient), current #depression (#Centre for #Epidemiological #Studies #Depression #Scale), and #lifetime #suicidality (Suicide Behavior Questionnaire-Revised). Results showed that burdensomeness and thwarted belonging significantly mediated the relationship between autistic traits and suicidal behavior. Both depression and autistic traits significantly predicted thwarted belonging and perceived burdensomeness. Autistic traits did not significantly moderate the relationship between suicidal behavior and thwarted belonging or perceived burdensomeness. Results suggest that the IPTS provides a useful framework for understanding the influence of autistic traits on suicidal behavior. However, the psychometric properties of these measures need be explored in those with clinically confirmed diagnosis of ASC.
لینک منبع 👇🏻(further reading)👇🏻
http://onlinelibrary.wiley.com/doi/10.1002/aur.1828/full
✅(در صورت جذابیت و علاقمندی به موضوع، مطلب را برای دیگران نیز بازنشر فرمایید).
📢کانال #دکترامیرمحمدشهسوارانی
🍃🌹🌸💐🌸🌹🍃
@DrAmirMohammadShahsavarani
Are #autistic #traits associated with #suicidality? A test of the #interpersonal-psychological
theory of #suicide in a #non-clinical #young adult sample
پژوهشگران روانشناسی دانشگاه کاونتری و دانشگاه بیرمنگام 🇬🇧، در تحقیقی که نتایج آن نیز به مراجع رسمی ایالات متحده 🇺🇸 و اتحادیه اروپا 🇪🇺 ارائه شده است، دریافتند افرادی که #رگه های #طیف #درخودماندگی (#ASD، #مشکلات #تعاملی و #ارتباطات #اجتماعی) دارند اما مشمول تشخیص این اختلالات نمی شوند در معرض خطر بالای خودکشی هستند.
🔬در این پژوهش که بصورت #آنلاین از 163 نفر بین 18 تا 30 ساله داوطلب به عمل آمد، شاخص های #فرسودگی، #افسردگی، #رگه های #آتیزم، #گرایش به #خودکشی، و #ارتباطات بین فردی مورد سنجش قرار گرفتند.
📚نتایج نشان دادند رگه های رفتارهای درخودمانده از طریق حساسات مورد #ظلم قرار گرفتن و #یاس/#ناامیدی منجر به افزایش چشمگیر رفتارهای خودکشی در جوانان می شوند.
Abstract
#Autism #spectrum #conditions (#ASC) has recently been associated with increased risk of #suicidality. However, no studies have explored how autistic traits may interact with current models of #suicidal #behavior in a #non-clinical #population. The current study therefore explored how #self-reported autistic traits interact with perceived #burdensomeness and #thwarted #belongingness in #predicting #suicidal behavior, in the context of the #Interpersonal-Psychological Theory of Suicide (#IPTS). 163 #young #adults (aged 18–30 years) completed an online #survey including measures of thwarted belonging and perceived burdensomeness (#Interpersonal #Needs #Questionnaire), self-reported autistic traits (#Autism #Spectrum #Quotient), current #depression (#Centre for #Epidemiological #Studies #Depression #Scale), and #lifetime #suicidality (Suicide Behavior Questionnaire-Revised). Results showed that burdensomeness and thwarted belonging significantly mediated the relationship between autistic traits and suicidal behavior. Both depression and autistic traits significantly predicted thwarted belonging and perceived burdensomeness. Autistic traits did not significantly moderate the relationship between suicidal behavior and thwarted belonging or perceived burdensomeness. Results suggest that the IPTS provides a useful framework for understanding the influence of autistic traits on suicidal behavior. However, the psychometric properties of these measures need be explored in those with clinically confirmed diagnosis of ASC.
لینک منبع 👇🏻(further reading)👇🏻
http://onlinelibrary.wiley.com/doi/10.1002/aur.1828/full
✅(در صورت جذابیت و علاقمندی به موضوع، مطلب را برای دیگران نیز بازنشر فرمایید).
📢کانال #دکترامیرمحمدشهسوارانی
🍃🌹🌸💐🌸🌹🍃
@DrAmirMohammadShahsavarani
Wiley
Are autistic traits associated with suicidality? A test of the interpersonal‐psychological theory of suicide in a non‐clinical…
Autism spectrum conditions (ASC) has recently been associated with increased risk of suicidality. However, no studies have explored how autistic traits may interact with current models of suicidal behavior...