Early life adversity and appetite hormones: The effects of smoking status, nicotine withdrawal, and relapse on ghrelin and peptide YY during smoking cessation

2021 ◽  
Vol 118 ◽  
pp. 106866
Author(s):  
Mustafa al'Absi ◽  
Briana DeAngelis ◽  
Motohiro Nakajima ◽  
Dorothy Hatsukami ◽  
Sharon Allen
2018 ◽  
Vol 98 ◽  
pp. 108-118 ◽  
Author(s):  
Mustafa al’Absi ◽  
Motohiro Nakajima ◽  
Andrine Lemieux

2019 ◽  
Author(s):  
Mary Elizabeth Zinn ◽  
Edward Huntley ◽  
Daniel Keating

Introduction. Early life adversity (ELA) can result in negative health-outcomes, including psychopathology. Evidence suggests that adolescence is a critical developmental period for processing ELA. Identity formation, which is crucial to this developmental period, may moderate the effect between ELA and psychopathology. One potential moderating variable associated with identity formation is Prospective Self, a latent construct comprised of future-oriented attitudes and behaviors.Methods. Participants are from the first wave of an ongoing longitudinal study designed to characterize behavioral and cognitive correlates of risk behavior trajectories. A community sample of 10th and 12th grade adolescents (N = 2017, 55% female) were recruited from nine public school districts across eight Southeastern Michigan counties in the United States. Data were collected in schools during school hours or after school via self-report, computer-administered surveys. Structural equation modeling was used in the present study to assess Prospective Self as a latent construct and to evaluate the relationship between ELA, psychopathology, and Prospective Self.Results. Preliminary findings indicated a satisfactory fit for the construct Prospective Self. The predicted negative associations between Prospective Self and psychopathology were found and evidence of moderation was observed for externalizing behavior problems, such that the effects of ELA were lower for individuals with higher levels of Prospective Self. Conclusion. These results support the role of Prospective Self in conferring resilience against externalizing behavior problems associated with ELA among adolescents. Keywords: Adolescence, Adverse Childhood Experiences, Psychopathology, Self-concept, Adolescent Health, Early Life Adversity


Author(s):  
Meg Dennison ◽  
Katie McLaughlin

Early-life adversity is associated with elevated risk for a wide range of mental disorders across the lifespan, including those that involve disruptions in positive emotionality. Although extensive research has evaluated heightened negative emotionality and threat processing as developmental mechanisms linking early-life adversity with mental health problems, emerging evidence suggests that positive emotions play an integral, but complex, role in the association of early-life adversity with psychopathology. This chapter identifies two pathways through which positive emotion influences risk for psychopathology following early-life adversity. First, experiences of early-life adversity may alter the development of the “positive valence system”, which in turn increases risk for psychopathology. Second, the association between adversity and psychopathology may vary as a function of individual differences in positive emotionality. We consider how the development of positive emotionality—measured at psychological, behavioral and neurobiological levels—may be altered by early-life adversity, creating a diathesis for psychopathology. We additionally review evidence for the role of positive emotion, measured at multiple levels, as a protective factor that buffers against the adverse impacts of adversity. In integrating these two roles, it is proposed that characteristics of environmental adversity, including developmental timing, duration, and type of adversity, may differentially impact the development of positive emotionality, leading to a better understanding of risks associated with specific adverse experiences. Methodological issues regarding the measurement of adverse environments as well as implications for early intervention and treatment are discussed.


2020 ◽  
Vol 9 (4) ◽  
pp. e001002
Author(s):  
Orestis Kanter Bax ◽  
Nadim Hakim ◽  
Michael Jeggo ◽  
Declan Phelan ◽  
Timothy Stevens ◽  
...  

Smoking tobacco is a major public health issue and a significant cause of increased mortality. People with a first episode of psychosis are more likely to smoke and the subgroup that goes on to have schizophrenia will have a significantly reduced life expectancy to the general population. The City & Hackney Early and Quick Intervention in Psychosis Team is a community mental health team at East London NHS Foundation Trust, providing outpatient care for adults presenting with first episode psychosis. This project aimed to increase the number of smoking cessation referrals from EQUIP to national smoking cessation services to 15% of the total team caseload over 6 months initially. A secondary measure was to complete an assessment of the smoking status for 90% of the caseload at all times. Change ideas were tested using plan-do-study-act cycles. A smoking cessation referral pathway was created and disseminated to the outpatient and inpatient services. The project was discussed at least monthly at the clinical team meeting. An education and skills building session was organised and took place at the team away day and an education drop-in session for patients was organised. The project was slow to take-off and patient participation was essential in driving progress. The aim was achieved at 23 months. A collateral benefit indicated that 25.7% of the total number of smokers had been recorded as having stopped smoking during the course of this project. This project demonstrates the effectiveness of quality improvement methodology facilitated by efficient leadership, collaborative teamwork, patient participation and persistence to address a complex problem that has significant consequences to patient health.


Author(s):  
Cheng-Chien Lai ◽  
Wei-Hsin Huang ◽  
Betty Chia-Chen Chang ◽  
Lee-Ching Hwang

Predictors for success in smoking cessation have been studied, but a prediction model capable of providing a success rate for each patient attempting to quit smoking is still lacking. The aim of this study is to develop prediction models using machine learning algorithms to predict the outcome of smoking cessation. Data was acquired from patients underwent smoking cessation program at one medical center in Northern Taiwan. A total of 4875 enrollments fulfilled our inclusion criteria. Models with artificial neural network (ANN), support vector machine (SVM), random forest (RF), logistic regression (LoR), k-nearest neighbor (KNN), classification and regression tree (CART), and naïve Bayes (NB) were trained to predict the final smoking status of the patients in a six-month period. Sensitivity, specificity, accuracy, and area under receiver operating characteristic (ROC) curve (AUC or ROC value) were used to determine the performance of the models. We adopted the ANN model which reached a slightly better performance, with a sensitivity of 0.704, a specificity of 0.567, an accuracy of 0.640, and an ROC value of 0.660 (95% confidence interval (CI): 0.617–0.702) for prediction in smoking cessation outcome. A predictive model for smoking cessation was constructed. The model could aid in providing the predicted success rate for all smokers. It also had the potential to achieve personalized and precision medicine for treatment of smoking cessation.


2021 ◽  
pp. 103836
Author(s):  
Tom J. Barry ◽  
Clara M. Villanueva-Romero ◽  
Jose V. Hernández-Viadel ◽  
Jorge J. Ricarte

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