{"title":"Implicit attitudes toward obesity-related cues and their relation to body mass index, psychosocial functioning, and health behavior.","authors":"Caroline Cummings, Tyler N Livingston","doi":"10.1037/hea0001404","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Differences in automatic cognitive processes exist among individuals with overweight and obesity, thus there is a need to expand our conceptualization of overweight and obesity to emphasize the predictive utility of these automatic processes, rather than focusing solely on behavioral outputs. Implicit association tests (IATs) may afford a noninvasive method of examining automatic preferences that might contribute to overweight and obesity; namely, preferences for unhealthy foods and sedentary behavior versus healthy foods and physical activity. The purpose of the current study was to examine whether implicit attitudes toward foods and physical activity differed based on body mass index (BMI) status. The relationships between implicit attitudes and key psychosocial factors and health behaviors were also examined.</p><p><strong>Method: </strong>Participants (<i>N</i> = 127) included undergraduate students with an average age of 19.05 years old (<i>SD</i> = 1.52). Average BMI of the sample was 24.20 (<i>SD</i> = 4.93); 33.8% met criteria for overweight or obesity. Participants completed an IAT and questionnaires.</p><p><strong>Results: </strong>There were no differences in implicit preferences based on BMI or BMI status. Overall, the sample demonstrated implicit preferences for healthy foods and active words, and preferences were not linked to the corresponding behavioral outputs, though preferences were linked to various indices of emotion and emotion regulation.</p><p><strong>Conclusions: </strong>Future research should explore an extended model to examine how implicit preferences might impact intentions to engage in protective versus risky obesity-related health behaviors, and the various psychosocial factors that might impact the translation of those preferences and intentions in actual behavioral outputs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/hea0001404","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Differences in automatic cognitive processes exist among individuals with overweight and obesity, thus there is a need to expand our conceptualization of overweight and obesity to emphasize the predictive utility of these automatic processes, rather than focusing solely on behavioral outputs. Implicit association tests (IATs) may afford a noninvasive method of examining automatic preferences that might contribute to overweight and obesity; namely, preferences for unhealthy foods and sedentary behavior versus healthy foods and physical activity. The purpose of the current study was to examine whether implicit attitudes toward foods and physical activity differed based on body mass index (BMI) status. The relationships between implicit attitudes and key psychosocial factors and health behaviors were also examined.
Method: Participants (N = 127) included undergraduate students with an average age of 19.05 years old (SD = 1.52). Average BMI of the sample was 24.20 (SD = 4.93); 33.8% met criteria for overweight or obesity. Participants completed an IAT and questionnaires.
Results: There were no differences in implicit preferences based on BMI or BMI status. Overall, the sample demonstrated implicit preferences for healthy foods and active words, and preferences were not linked to the corresponding behavioral outputs, though preferences were linked to various indices of emotion and emotion regulation.
Conclusions: Future research should explore an extended model to examine how implicit preferences might impact intentions to engage in protective versus risky obesity-related health behaviors, and the various psychosocial factors that might impact the translation of those preferences and intentions in actual behavioral outputs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).