کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10143140 | 1646153 | 2018 | 43 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Training and testing for a transformation of fear and avoidance functions using the Implicit Relational Assessment Procedure: The first study
ترجمه فارسی عنوان
آموزش و تست برای تبدیل توابع ترس و اجتناب با استفاده از روش ارزیابی وابستگی نامتجانس: اولین مطالعه
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موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم دامی و جانورشناسی
چکیده انگلیسی
Experiment 1 aimed to establish “fearful” and “pleasant” functions for arbitrary stimuli (geometric shapes) by relating those stimuli to pictures of spiders and pets using a training version of the Implicit Relational Assessment Procedure (IRAP). The transformation of these functions for the arbitrary stimuli was assessed by exposing participants to a 'traditional' version of the IRAP, the Fear-IRAP employed by Leech et al. (2016, 2017). A broadly similar pattern of response biases was recorded for the Fear-IRAP as had been observed in the previously published studies. Experiment 1 thus supported the assumed but untested assumption that the relational context provided by the IRAP may both serve to establish and reveal fear-related response biases in arbitrary stimuli. A second experiment attempted to replicate the effects observed in Experiment 1 but using pictures of 'unfamiliar' Australian marsupials as arbitrary stimuli. The pattern of results obtained in Experiment 2 failed to replicate the pattern observed in Experiment 1, or that reported in the previously published studies by Leech et al. Overall, the findings suggest a possibly important boundary condition for the IRAP as a training and/or testing context for establishing fear-related response biases for arbitrary stimuli.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Behavioural Processes - Volume 157, December 2018, Pages 24-35
Journal: Behavioural Processes - Volume 157, December 2018, Pages 24-35
نویسندگان
Aileen Leech, Jaber Bouyrden, Nathalie Bruijsten, Dermot Barnes-Holmes, Ciara McEnteggart,