Addiction Mindsets and Psychological Processes of Quitting Smoking

Background: Lay belief systems about the malleability of human attributes have been shown to impact behavior change in multiple domains. Addiction mindset—i.e., beliefs about the permanence (vs. malleability) of addiction — may affect cigarette smokers’ ability to quit, but this has never been examined. Objectives: The aims of the present research were to develop a measure of addiction mindset (study 1) and examine its associations with various psychological aspects of quitting smoking (study 2). Methods: In Study 1, using factor analysis of current smokers’ and nonsmokers’ (n?=?600) responses to 22 items designed to measure addiction mindset, we developed a reliable six-item Addiction Mindset Scale (AMS). In Study 2, adult smokers (n?=?200) completed the AMS, and measures of a number of psychological processes related to smoking. Results: Higher scores on the AMS, indicative of the belief that addiction is malleable (referred to as a growth mindset), were positively and significantly associated with greater motivation to quit, greater commitment to quitting, greater self-efficacy to abstain, less attribution of failure to lack of ability to change addiction, and fewer self-reported barriers to cessation (all p’s < .05). Conclusions: The results of this study show a relationship between the beliefs about the permanence of addiction and psychological processes relevant to quitting smoking. The findings underscore the potential of future research exploring how addiction mindsets relate to successful smoking cessation as well as other types of addictive behavior and how they can be applied to change people’s behavior.     

HPLC-MS Method for Simultaneous Quantitative Determination of an Innovative Russian Gestagen and its Metabolites in Rat and Rabbit Blood Sera

Pharmaceutical Chemistry Journal - An HPLC-MS method for simultaneous quantitative determination of a novel gestagenic pharmaceutical and two of its metabolites in rat and rabbit blood sera was...     

Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

The majority of hip fractures in the elderly are the result of a fall from standing or from a lower height. Current injury models focus mostly on femur strength while neglecting subject-specific loading. This article presents an injury modeling strategy for hip fractures related to sideways falls that takes subject-specific impact loading into account. Finite element models (FEMs) of the human body were used to predict the experienced load and the femoral strength in a single model. We validated these models for their predicted peak force, effective pelvic stiffness, and fracture status against matching ex vivo sideways fall impacts (n = 11) with a trochanter velocity of 3.1 m/s. Furthermore, they were compared to sideways impacts of volunteers with lower impact velocities that were previously conducted by other groups. Good agreement was found between the ex vivo experiments and the FEMs with respect to peak force (root mean square error [RMSE] = 10.7%, R² = 0.85) and effective pelvic stiffness (R² = 0.92, RMSE = 12.9%). The FEMs were predictive of the fracture status for 10 out of 11 specimens. Compared to the volunteer experiments from low height, the FEMs overestimated the peak force by 25% for low BMI subjects and 8% for high BMI subjects. The effective pelvic stiffness values that were derived from the FEMs were comparable to those derived from impacts with volunteers. The force attenuation from the impact surface to the femur ranged between 27% and 54% and was highly dependent on soft tissue thickness (R² = 0.86). The energy balance in the FEMS showed that at the time of peak force 79% to 93% of the total energy is either kinetic or was transformed to soft tissue deformation. The presented FEMs allow for direct discrimination between fracture and nonfracture outcome for sideways falls and bridge the gap between impact testing with volunteers and impact conditions representative of real life falls. © 2019 American Society for Bone and Mineral Research.