Compared to smokers in the general population, smokers with schizophrenia smoke more cigarettes per day and have higher nicotine dependence and biochemical indicators of nicotine intake. They also have more intense smoking topography and greater positive smoking expectancies. Little is known about the relationship between smoking and schizotypy, defined as the personality organization reflecting a vulnerability to schizophrenia-spectrum pathology. This study assessed schizotypy symptoms, smoking characteristics and behaviors, and smoking expectancies in young adults with psychometrically defined schizotypy and demographically matched controls without schizotypy. Smokers with schizotypy had higher nicotine dependence and smoked more cigarettes per week compared to control smokers. They were also more likely to endorse greater positive consequences (i.e., improved state enhancement, stimulation, social facilitation, taste/sensorimotor manipulation, reduced negative affect and boredom) and fewer negative consequences of smoking. Smokers with schizotypy and control smokers did not differ on smoking topography or carbon monoxide levels. This is the first known study to investigate relationships between these smoking-related variables in smokers with schizotypy. Individuals with schizotypy possessed certain smoking-related characteristics and smoking expectancies similar to those with schizophrenia. This offers preliminary insight into unique smoking-related factors among individuals with schizotypy and highlights the importance of continued research in this area.
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http://dx.doi.org/10.1016/j.psychres.2012.11.032 | DOI Listing |
Anal Chem
January 2025
Forensic Research & Development Department, Institute of Environmental Science and Research, PO Box 50348, Porirua 5240, New Zealand.
Electrochemical aptamer-based biosensors (E-aptasensors) are emerging platforms for point-of-care (POC) detection of complex biofluids. Human saliva particularly offers a noninvasive matrix and unprecedented convenience for detecting illicit drugs, such as cocaine. However, the sensitivity of cocaine E-aptasensors is significantly compromised in saliva.
View Article and Find Full Text PDFNicotine Tob Res
December 2024
Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Introduction: Prior research suggests that the e-Cigarette Wisconsin Inventory of Smoking Dependence Motives (e-WISDM) distinguishes primary (e-PDM) and secondary dependence (e-SDM), however, there is little research on these e-WISDM dimensions and prior research comprised dual users (using cigarettes and e-cigarettes) and those using older generations of e-cigarettes.
Methods: Those exclusively using contemporary e-cigarettes (N = 164) completed the e-WISDM and a laboratory self-administration session and rated pre-use expectancies and post-use experiences.
Results: Only a 1-factor model limited to the primary scales (Automaticity, Tolerance, Craving, Loss of Control) achieved good model fit.
Rom J Morphol Embryol
November 2024
Discipline of Anatomy and Embryology, Department of Morpho-Functional Sciences I, Faculty of Medicine, Grigore T. Popa University of Medicine and Pharmacy, Iaşi, Romania;
Metastases are the most common tumors of the spine. As an important increase in the annual incidence of spinal metastases (SMs) has been observed in the last decade, the aim of this study was to describe the epidemiology and histopathological types of SMs surgically treated in the Neurosurgery Clinics of a Regional Hospital in North-Eastern Romania over a period of five years, in order to define a certain tumor profile that would benefit from an early screening. We retrospectively evaluated 115 adult patients, searching for demographic data (gender and age of the patients), primary tumor characteristics (location and histological type), topography of the SMs, and the time interval between the diagnosis of the primary tumor and the surgery for the SMs.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Department of Biomedical Engineering, Lawrence Technological University, 21000 W 10 Mile Road, Southfield, MI 48075, USA.
To monitor health risks associated with vaping, we introduce a multi-spectral optical sensor powered by machine learning for real-time characterization of electronic cigarette aerosols. The sensor can accurately measure the mass of particulate matter (PM) in specific particle size channels, providing essential information for estimating lung deposition of vaping aerosols. For the sensor's input, wavelength-specific optical attenuation signals are acquired for three separate wavelengths in the ultraviolet, red, and near-infrared range, and the inhalation pressure is collected from a pressure sensor.
View Article and Find Full Text PDFJAMA Netw Open
November 2024
Department of Medicine, Yale School of Medicine, New Haven, Connecticut.
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