This study examined the extent to which shared versus specific features across multiple manifestations of psychological symptoms (depression, anxiety, ADHD, aggression, alcohol misuse) associated with cigarettes per day. Subsequently, we investigated whether negative- (i.e., withdrawal relief) and positive- (i.e., pleasure enhancement) reinforcement smoking motivations mediated relations. Adult daily smokers (N = 338) completed self-report measures and structural equation modeling was used to construct a 3-factor (low positive affect-negative affect-disinhibition) model of affective and behavioral symptoms and to test relations of each latent factor (shared features) and indicator residual (specific features) to smoking level. Shared dimensions of low positive affect, negative affect, and disinhibition associated with smoking rate. Negative-reinforcement smoking mediated the link between latent negative affect and heavier daily smoking. Specific features of psychological symptoms unique from latent factors were generally not associated with cigarettes per day. Features shared across several forms of psychological symptoms appear to underpin relations between psychological symptoms and smoking rate.
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http://dx.doi.org/10.1007/s10865-014-9597-y | DOI Listing |
EClinicalMedicine
October 2024
Centre for Psychedelic Research, Division of Psychiatry, Department Brain Sciences, Imperial College London, United Kingdom.
Background: Psilocybin therapy (PT) produces rapid and persistent antidepressant effects in major depressive disorder (MDD). However, the long-term effects of PT have never been compared with gold-standard treatments for MDD such as pharmacotherapy or psychotherapy alone or in combination.
Methods: This is a 6-month follow-up study of a phase 2, double-blind, randomised, controlled trial involving patients with moderate-to-severe MDD.
World J Clin Cases
January 2025
Department of Neurology, Guizhou Medical University, Guiyang 550004, Guizhou Province, China.
Dementia is a group of diseases, including Alzheimer's disease (AD), vascular dementia, Lewy body dementia, frontotemporal dementia, Parkinson's disease dementia, metabolic dementia and toxic dementia. The treatment of dementia mainly includes symptomatic treatment by controlling the primary disease and accompanying symptoms, nutritional support therapy for repairing nerve cells, psychological auxiliary treatment, and treatment that improves cognitive function through drugs. Among them, drug therapy to improve cognitive function is important.
View Article and Find Full Text PDFInternet Interv
December 2024
Oxford Centre for Anxiety Disorders and Trauma (OxCADAT), Department of Experimental Psychology, University of Oxford, The Old Rectory, Paradise Square, Oxford OX1 1TW, UK.
Background: Sudden gains are large symptom improvements between consecutive therapy sessions. They have been shown to occur in randomised controlled trials of internet-delivered psychological interventions, but little is known about their occurrence when such treatments are delivered in routine clinical practice.
Objective: This study examined the occurrence of sudden gains in a therapist-guided internet-delivered Cognitive Therapy intervention for social anxiety disorder (iCT-SAD) delivered in the UK NHS talking therapies for anxiety and depression (formerly known as IAPT services).
EClinicalMedicine
August 2024
Department of Psychosomatic Medicine and Psychotherapy, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
Background: Despite the immense impact of Long COVID on public health and those affected, its aetiology remains poorly understood. Findings suggest that psychological factors such as depression contribute to symptom persistence alongside pathophysiological mechanisms, but knowledge of their relative importance is limited. This study aimed to synthesise the current evidence on psychological factors potentially associated with Long COVID and condition-relevant outcomes like quality of life.
View Article and Find Full Text PDFEClinicalMedicine
August 2024
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom.
Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.
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