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361.
Gregory S. Chasson Casey R. Guillot Michael J. Zvolensky Madalyn M. Liautaud Norman B. Schmidt Adam M. Leventhal 《Cognitive behaviour therapy》2020,49(5):385-397
ABSTRACT Tobacco addiction and obsessive-compulsive symptoms (OCS; intrusive thoughts or impulses that cause distress and rituals) are both mediated by compulsivity and negative reinforcement. Little evidence exists to guide theory, research, treatment, and population-based prevention of this co-occurrence. We propose a conceptual model of OCS-smoking co-occurrence in which smokers with elevated OCS capitalize on smoking to assuage OCS. This secondary analysis examined associations between OCS levels and self-reported smoking motives that are model-concordant: i) negative reinforcement—smoking for relief; ii) sensorimotor—benefits of behaviors and sensations of the tobacco self-administration ritual; and iii) habitual—smoking without conscious control. A community sample of cigarette smokers enrolled in a cessation trial (N = 458; 47.2% female; M age = 36.9; SD = 13.6) completed pre-quit self-report measures of OCS levels and smoking motives. Regression models adjusted for sociodemographic covariates and non-OCS psychopathologies indicated that OCS level was positively associated with each model-concordant motive. OCS level was also correlated with tobacco dependence severity and greater withdrawal symptom severity experienced during previous quit attempts. Those with higher OCS report greater motivation to smoke for negative reinforcement, sensorimotor behavioral-ritualistic, habit/automaticity, and stimulation reasons. Further examination of the proposed model of OCS-smoking co-occurrence is warranted to guide theory and intervention for this population. 相似文献
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Bonnie A. Clough Sonia M. Nazareth Leanne M. Casey 《British Journal of Guidance & Counselling》2020,48(3):347-359
ABSTRACT International students may have less understanding and awareness of mental health issues and appear unlikely to seek help. The purpose of the current study was to construct and evaluate a brief online educational intervention designed to increase mental health literacy (MHL) and help-seeking among international tertiary students studying in Australia. The intervention was tested among 45 international tertiary students (undergraduate and postgraduate), who were randomly allocated to control and intervention conditions. The intervention led to significant improvements in help-seeking attitudes, particularly in stigmatising attitudes. No significant effects were found for MHL or help-seeking intentions. A brief educational intervention can improve help-seeking attitudes among international tertiary students. Future research may focus on establishing optimal intervention dosage. 相似文献
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Casey P. Homan 《Journal of Contemporary Religion》2019,34(3):551-569
ABSTRACTResearch at the nexus of attachment theory and religion has generally been constrained both by data limitations and by a view of attachment style as fixed early in life. I use three waves of data to test key hypotheses from this literature in new ways. Closeness to mother and closeness to father serve as proxies for attachment to parents and closeness to God serves as a proxy for attachment to God. The correspondence hypothesis predicts that people who feel closer to their parents feel closer to God, the compensation hypothesis predicts that people lacking a parent feel closer to God, and the socialized correspondence hypothesis predicts that people with nonreligious parents will feel less close to God if they feel closer to their parents. I find strong evidence in favor of the correspondence hypothesis, but I find no evidence in favor of the compensation hypothesis or the socialized correspondence hypothesis. 相似文献
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Casey Casalnuovo Kevin Lee Hulin Wang Prem Devanbu Emily Morgan 《Cognitive Science》2020,44(12):e12921
Source code is a form of human communication, albeit one where the information shared between the programmers reading and writing the code is constrained by the requirement that the code executes correctly. Programming languages are more syntactically constrained than natural languages, but they are also very expressive, allowing a great many different ways to express even very simple computations. Still, code written by developers is highly predictable, and many programming tools have taken advantage of this phenomenon, relying on language model surprisal as a guiding mechanism. While surprisal has been validated as a measure of cognitive load in natural language, its relation to human cognitive processes in code is still poorly understood. In this paper, we explore the relationship between surprisal and programmer preference at a small granularity—do programmers prefer more predictable expressions in code? Using meaning-preserving transformations, we produce equivalent alternatives to developer-written code expressions and run a corpus study on Java and Python projects. In general, language models rate the code expressions developers choose to write as more predictable than these transformed alternatives. Then, we perform two human subject studies asking participants to choose between two equivalent snippets of Java code with different surprisal scores (one original and transformed). We find that programmers do prefer more predictable variants, and that stronger language models like the transformer align more often and more consistently with these preferences. 相似文献