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1000
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Abstract/Summary
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Imaginal retraining is a variant of approach bias modification and transfers the method into one's own mind. As the technique contains multiple elements, this pilot study aimed to dismantle which of its components is most efficient in reducing craving for high-calorie food. A total of 113 women were randomly allocated to one out of six conditions containing a short intervention to mentally manipulate a picture displaying high-calorie foods. Four of the interventions involved different combinations of elements of the imaginal retraining technique, while the remaining two conditions comprised thought suppression or merely observing a picture. Participants rated their level of craving, as well as three pictures containing healthy and unhealthy foods regarding their pleasantness before and after the interventions took place. Within-group changes were assessed with paired t-tests (in case of non-normal data Wilcoxon paired t-tests) and between-group differences with one-way ANOVAs (non-parametric Kruskal-Wallis tests). A trend level reduction in craving was found in the imaginal retraining condition with and without a movement. A post hoc analysis of both conditions joint together showed a statistically significant reduction in craving. In addition, positive picture appraisal for unhealthy foods was significantly reduced in both imaginal retraining conditions (with and without movement) with medium to large effect sizes. This study demonstrated that imaginal retraining with an arm movement can reduce craving and picture appraisal for high-calorie foods significantly in a one-time application. It is a promising technique to reduce appraisal for unhealthy high-calorie foods. Future studies should repeat the experiment in situations of high craving and allow for a personalized selection of stimuli.
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1000
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Hinweis
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DeepGreen-ID: 649a8fd6929840d48881121ae4ea462f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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