The primary foci of the study were exploration of the linkage between cognitive and autonomic inflexibility of worry and generalized anxiety disorder (GAD) and examination of the effects of an analog cognitive restructuring task on this relationship. Cardiac responses of GAD and non-GAD participants were measured to examine the sympathetic and parasympathetic effects of worry and cognitive challenge. Diagnostic groups of undergraduate students were determined via administration of a structured interview, yielding a GAD group (n=16) and a control group (n=19) of individuals without GAD, depression, or panic disorder diagnoses. Cardiac autonomic responses were acquired via electrocardiogram during rest, worry, and cognitive challenge conditions by an experimenter blind to diagnosis. Metrics were compared between the two groups and across the three conditions. Individuals diagnosed with GAD did not differ significantly from controls on autonomic indices. Worry was associated with significantly decreased parasympathetic influence and increased sympathetic activity. Cognitive challenge did not result in significant increased cardiac responsivity. The results indicate that worry behavior is associated with decreased vagal activity, suggest a linkage between autonomic and cognitive inflexibility, and provide further suggestions for improving protocols to assess the autonomic effects of cognitive therapy techniques.

Background High quality serious illness communication requires good understanding of patients’ values and beliefs for their treatment at end of life. Natural Language Processing (NLP) offers a reliable and scalable method for measuring and analyzing value- and belief-related features of conversations in the natural clinical setting. We use a validated NLP corpus and a series of statistical analyses to capture and explain conversation features that characterize the complex domain of moral values and beliefs. The objective of this study was to examine the frequency, distribution and clustering of morality lexicon expressed by patients during palliative care consultation using the Moral Foundations NLP Dictionary. Methods We used text data from 231 audio-recorded and transcribed inpatient PC consultations and data from baseline and follow-up patient questionnaires at two large academic medical centers in the United States. With these data, we identified different moral expressions in patients using text mining techniques. We used latent class analysis to explore if there were qualitatively different underlying patterns in the PC patient population. We used Poisson regressions to analyze if individual patient characteristics, EOL preferences, religion and spiritual beliefs were associated with use of moral terminology. Results We found two latent classes: a class in which patients did not use many expressions of morality in their PC consultations and one in which patients did. Age, race (white), education, spiritual needs, and whether a patient was affiliated with Christianity or another religion were all associated with membership of the first class. Gender, financial security and preference for longevity-focused over comfort focused treatment near EOL did not affect class membership. Conclusions This study is among the first to use text data from a real-world situation to extract information regarding individual foundations of morality. It is the first to test empirically if individual moral expressions are associated with individual characteristics, attitudes and emotions.

Articles about systematic desensitization that appeared in mainstream behavior therapy journals between the years 1970 and 2002 were counted. Graphic displays of the data point to a sudden and lasting decline of interest in systematic desensitization among academics and researchers. A questionnaire concerning clinical use of orthodox systematic desensitization was mailed to 310 selected providers. Returns from 171 of those providers show that use of systematic desensitization has declined but continues to be fairly widespread. The decline of interest in systematic desensitization is explained: arguments are offered that revitalized interest would be beneficial but is not likely to occur.

Background High quality serious illness communication requires good understanding of patients' values and beliefs for their treatment at end of life. Natural Language Processing (NLP) offers a reliable and scalable method for measuring and analyzing value- and belief-related features of conversations in the natural clinical setting. We use a validated NLP corpus and a series of statistical analyses to capture and explain conversation features that characterize the complex domain of moral values and beliefs. The objective of this study was to examine the frequency, distribution and clustering of morality lexicon expressed by patients during palliative care consultation using the Moral Foundations NLP Dictionary.Methods We used text data from 231 audio-recorded and transcribed inpatient PC consultations and data from baseline and follow-up patient questionnaires at two large academic medical centers in the United States. With these data, we identified different moral expressions in patients using text mining techniques. We used latent class analysis to explore if there were qualitatively different underlying patterns in the PC patient population. We used Poisson regressions to analyze if individual patient characteristics, EOL preferences, religion and spiritual beliefs were associated with use of moral terminology.Results We found two latent classes: a class in which patients did not use many expressions of morality in their PC consultations and one in which patients did. Age, race (white), education, spiritual needs, and whether a patient was affiliated with Christianity or another religion were all associated with membership of the first class. Gender, financial security and preference for longevity-focused over comfort focused treatment near EOL did not affect class membership.Conclusions This study is among the first to use text data from a real-world situation to extract information regarding individual foundations of morality. It is the first to test empirically if individual moral expressions are associated with individual characteristics, attitudes and emotions.