Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Macrodosing To Microdosing With Psychedelics: Clinical, Social, And Cultural Perspectives, Ayse Ceren Kaypak, Amir Raz

Psychology Faculty Articles and Research

To date, the clinical and scientific literature has best documented the effects of classical psychedelics, such as lysergic acid diethylamide (LSD), psilocybin, and dimethyltryptamine (DMT), in typical quantities most often associated with macrodosing. More recently, however, microdosing with psychedelics has emerged as a social trend and nascent therapeutic intervention. This variation in psychedelic practice refers to repeat, intermittent ingestion of less-than-macrodose amounts that do not cause the effects associated with full-blown “trips”. Microdosing paves the road to incorporating psychedelic drugs into a daily routine while maintaining, or even improving, cognitive and mental function. Unlike macrodosing with psychedelics, the influence of …

A Multivariable Model Of Parent Satisfaction, Pain, And Opioid Administration In A Pediatric Emergency Department, Candice D. Donaldson, Thomas W. Heyming, Louis Ehwerhemuepha, Brooke N. Jenkins, Michelle A. Fortier, William Feaster, Zeev N. Kain

Psychology Faculty Articles and Research

Introduction: Children and adolescents are not impervious to the unprecedented epidemic of opioid misuse in the United States. In 2016 more than 88,000 adolescents between the ages of 12–17 reported misusing opioid medication, and evidence suggests that there has been a rise in opioid-related mortality for pediatric patients. A major source of prescribed opioids for the treatment of pain is the emergency department (ED). The current study sought to assess the complex relationship between opioid administration, pain severity, and parent satisfaction with children’s care in a pediatric ED.

Methods: We examined data from a tertiary pediatric care facility. A health …

Identifying Depression In The National Health And Nutrition Examination Survey Data Using A Deep Learning Algorithm, Jihoon Oh, Kyongsik Yun, Uri Maoz, Tae-Suk Kim, Jeong-Ho Chae

Psychology Faculty Articles and Research

Background

As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depression has remained challenging. Deep-learning algorithms can be applied to assess the factors leading up to prevalence and clinical manifestations of depression.

Methods

Customized deep-neural-network and machine-learning classifiers were assessed using survey data from 19,725 participants from the NHANES database (from 1999 through 2014) and 4949 from the South Korea NHANES (K-NHANES) database in 2014.

Results

A deep-learning algorithm showed area under the receiver operating characteristic curve (AUCs) …