Dataset Information

The Phenomenology of Hair Pulling Urges in Trichotillomania: A Comparative Approach.

ABSTRACT: Trichotillomania is a disorder characterized by recurrent urges to pull out one's hair, but the experiential characteristics of hair pulling urges are poorly understood. This study used a comparative approach to understand the subjective phenomenology of hair pulling: participants with trichotillomania symptoms were asked about their hair pulling urges as well as their urges to eat unhealthy foods. Participants who reported experiencing problematic unhealthy food urges were identified and asked to compare the phenomenological characteristics of their hair pulling and unhealthy food urges across a variety of dimensions. Results revealed significant differences for only some urge properties measured, and differences that existed were small to moderate in magnitude. Qualitative comparisons of the two urges revealed situational characteristics of hair pulling that could explain these small to moderate differences between the two urges. We conclude that hair pulling urges may be more comparable to ordinary urges such as unhealthy food urges than one might expect, but that hair pulling urges may nevertheless be rated as slightly more severe due to situational characteristics of these urges. This conception may improve clinician and lay understanding of the condition, assist with destigmatization efforts, and facilitate the development of treatment strategies.

SUBMITTER: Madjar S

PROVIDER: S-EPMC4759292 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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The Phenomenology of Hair Pulling Urges in Trichotillomania: A Comparative Approach.

Madjar Shai S Sripada Chandra S CS

Frontiers in psychology 20160219

Trichotillomania is a disorder characterized by recurrent urges to pull out one's hair, but the experiential characteristics of hair pulling urges are poorly understood. This study used a comparative approach to understand the subjective phenomenology of hair pulling: participants with trichotillomania symptoms were asked about their hair pulling urges as well as their urges to eat unhealthy foods. Participants who reported experiencing problematic unhealthy food urges were identified and asked ...[more]

PMID: 26925017

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Project description:Background and objectiveSmoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states.MethodsTo test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision.ResultsThe outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications.ConclusionsIn conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions.

Dataset Information

The Phenomenology of Hair Pulling Urges in Trichotillomania: A Comparative Approach.

Publications

The Phenomenology of Hair Pulling Urges in Trichotillomania: A Comparative Approach.

Similar Datasets

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