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نتیجه جستجو - Latent class analysis

تعداد مقالات یافته شده: 5
ردیف عنوان نوع
1 Missed opportunities: Arrest and court touchpoints for individuals who fatally overdosed in Philadelphia in 2016
فرصت های از دست رفته: دستگیری و نقاط تماس دادگاه برای افرادی که در سال 2016 در فیلادلفیا بیش از حد دوز مصرف کرده بودند-2020
Background: Many studies document high risk of fatal overdose after incarceration. Few explore earlier touchpoints in criminal justice processes, like arrests and court hearings. Understanding these touchpoints is important for several reasons. Arrest and adjudicatory processes are harmful even when not resulting in incarceration. Arrests and criminal hearings also may reflect changes in overdose-related risk factors like transitions in employment and housing stability. Moreover, knowledge about these touchpoints contextualizes debate about the implementation of court-based programs like Drug Treatment Courts. This study described the incidence and accumulation of touchpoints for people who fatally overdosed in Philadelphia in 2016, and depicted how touchpoint incidence and characteristics interface with court-program eligibility. Methods: Criminal court documents were obtained for all individuals who fatally overdosed in Philadelphia in 2016 from the Philadelphia Medical Examiners Office. The characteristics of arrests and court hearings were abstracted to compile lifetime criminal histories. Latent class analysis was performed to identify whether these histories followed observably distinct patterns. Results: In 2016, 907 people fatally overdosed in Philadelphia. Of these, 605 had at least one or more of 3,926 arrests and 3,822 hearings over their lifetime. There were 488 arrests and 533 hearings in the two years before death, with public disorder charges especially common closer to death. Less than 20% of these hearings resulted in custodial sentences. Of individuals with touchpoints, only nine participated in Drug Treatment Court, consistent with findings that most individuals were ineligible. Latent class analysis suggested five distinguishable patterns in age, timing, and characteristics of touchpoints. Conclusions: The type and frequency of touchpoints preceding fatal overdose reflect a period of complex vulnerability. Few individuals qualified for court-based programming, underscoring the limitations of supporting this population in specialized court settings. Reducing incidence and improving the health impact of criminal justice touchpoints remain important public health priorities.
Keywords: Criminal justice | Opioid | Overdose death | Drug court | Latent class analysis
مقاله انگلیسی
2 Deadly violence in Sweden: Profiling offenders through a latent class analysis
خشونت مرگبار در سوئد: پروفایل مجرمان از طریق تجزیه و تحلیل کلاس پنهان-2020
Background: Sweden has in recent years witnessed increasing rates of firearm-related violence and homicide, which has contributed to increased rates of deadly violence. Attempts to profile offenders committing such crimes are of major importance, because such efforts may contribute to better preventive measures. We therefore aimed to study the characteristics of individuals convicted and/or suspected of homicide, attempted homicide, preparation to commit homicide as well as conspiration to commit homicide (for simplicity called homicide+) in Sweden. Methods: By using information from the Swedish Crime Register and the Swedish Criminal Suspect Register, individuals being 15–60 years old and convicted and/or suspected of homicide+ between 2000 and 2015 were included in the study. Using these registers and also other population and health care registers, information on previous criminality, substance abuse, and psychiatric disorders were added to the Latent Class Analysis (LCA) that was used to identify latent classes of individuals convicted and/or suspected for homicide+. In addition, several individual variables were added for validation purposes. Results: A total of 14,466 individuals were included in the analysis. The majority were male (n = 12,802; 88.5%) and Swedish-born with Swedish-born parents (n=8247; 57.0%). The LCA identified three classes where Conviction Class (CC) contained mostly convicted individuals whereas Mixed Class A (MCA) and Mixed Class B (MCB) contained almost equal rates of both convicted and suspected individuals. The CC was characterized by individuals with low rates of previous criminality, substance abuse and psychiatric disorders. The MCA and the MCB were characterized by individuals with higher rates of previous criminality, substance abuse, and psychiatric disorders as well as lower education and worse economy in comparison with the CC. Conclusion: While MCA and MCB may be constituted by “traditional” criminals often well known by the police and/or the social authorities, the CC was mainly constituted by convicted offenders who may more easily escape the radar of the authorities.
Keywords: Deadly violence | Homicide | Offender characteristics | Sweden | Latent class analysis
مقاله انگلیسی
3 A latent profile analysis of exposure to community violence and peer delinquency in African American adolescents
یک تحلیل نهان پروفایلی روی افشای جرم اجتماعی و همکاری در بزهکاری در نوجوانان آفریقایی آمریکایی-2018
Aims Person-based analyses have demonstrated wide variability among the levels of exposure to community violence (ECV) experienced by youth in disadvantaged communities. In addition, social network research has found that violence victimization tends to occur primarily among a small social group, demonstrating that levels of peer delinquency may be a factor that distinguishes among youth who experience high and low levels of ECV. Methods The current study utilized latent class analysis to examine profiles of ECV and peer delinquency in a sample of 618 African American adolescents (54.7% female; mean age = 15.8, SD = 1.41), and the relationship these profiles have to adaptive and maladaptive outcomes. Results Results demonstrated that levels of ECV and peer delinquency vary significantly among these youth, and profile membership predicts levels of delinquency, aggression, future orientation, and self-esteem. Conclusion Research and clinical implications are discussed.
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مقاله انگلیسی
4 مسئولیت گسترده تولید کننده: تاثیر ابعاد سازمانی بر روی جمع آوری زباله های تجهیزات الکتریکی و الکترونیک از خانواده ها
سال انتشار: 2017 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 26
"مسئولیت گسترده تولید کننده" (EPR) از دهه 2000، به عنوان ستون فقرات مدیریت چرخه عمر محصول در اروپا شده است. متاسفانه، اجرای "مسئولیت گسترده تولید کننده" چندین اثر بر روی زنجیره تامین دارد و بنابراین پیامدهای آن همیشه به راحتی قابل مدیریت نیست. اگرچه چندین مطالعه به بررسی مثالهای مختلفی درداخل اروپا پرداخته اند، اما عوامل تعیین کننده سومندی مدیریت "مسئولیت گسترده تولید کننده" هنوزهم کاملا" درک نشده است. این تحقیق به دنبال پر کردن این شکاف از طریق استفاده از تحلیل های کمّی جهت بررسی اینکه چگونه مسائل کلیدی به آن مربوط می شوند، می باشد: جابجایی های رهنمودی WEEE (زباله تجهیزات و وسایل الکتریکی و الکترونیک) و شرایط سازمانی پذیرفته شده توسط هر ایالت عضو بر نتایج به دست آمده در آن ایالت های عضو درمورد جمع آوری این تجهیزات از خانواده ها اثر می گذارد. به صورت جزئی تر، یک تحلیل کلاسی مخفی (LCA) برای تحلیل راهبردهای مختلف مدیریت "مسئولیت گسترده تولید کننده" بر مبنای شرایط سیاست، ساختار زنجیره تامین، و بازدهی جمع آوری زباله الترونیک از خانواده ها، استفاده شده است. نتایج ارتباط قوی بین واگذاری مسئولیت و مدل سازمانی پذیرفته شده در ایالت های عضو و بازدهی مربوط به تجهیزات خانوارهای کوچک را پررنگ می کند. نتایج نشانگر نیاز به هماهنگی قوی تر "مسئولیت گسترده تولید کننده" و سیاست های زباله ای به منظور دستیابی به سطوح کافی از جمع آوری زباله های تجهیزات الکتریکی و الکترونیک، نیاز به تشریح واضح مسئولیت های هر بخش از زنجیره تامین و همچنین اهمیت "خانه های تمیز کننده" در وساطت کردن اثرات رقابت کوته نگرانه بین طرح های جمعی می باشد.
کلیدواژه ها: مدیریت پایدار زنجیره تامین | مسئولیت گسترده تولید کننده | زباله الکترونیک | بهره وری منبع | سیاست محیطی
مقاله ترجمه شده
5 A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk
یک روش مدل سازي تحلیلی طبقه بندي کم عمق برای تحلیل تصادفات بزرگراه شهری-2017
Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which would further refine the design of Active Traffic Management System (ATMS). However, the majority of the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk estimation while recent studies proved that crash occurrence risk was affected by the various alignment features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter logistic regression technique; data from Shanghai urban expressway system were employed to conduct the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally, benefits of the proposed hybrid LCA approach were discussed.
Keywords: Crash risk analysis | Latent class analysis | Bayesian random parameter model | Unobserved heterogeneity
مقاله انگلیسی
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