Stuart W Flint, Ezra Goldberg, Mohammad Kaykanloo, Stuart Sherman, Duncan Radley, Sarah R Kingsbury, Louisa Ells
{"title":"性格与英国国民保健服务低卡路里饮食计划的生活经历有关:一项试点研究。","authors":"Stuart W Flint, Ezra Goldberg, Mohammad Kaykanloo, Stuart Sherman, Duncan Radley, Sarah R Kingsbury, Louisa Ells","doi":"10.1111/cob.70003","DOIUrl":null,"url":null,"abstract":"<p><p>This pilot study explored the use of a novel behavioural artificial intelligence (AI) tool to examine whether personality is associated with the lived experience of the NHS England launched a low calorie diet (LCD). A cross-sectional survey was disseminated to service users to gather data on emotional wellbeing, physical activity, pain, motivation to manage diabetes, motivation to lose weight, rating of total diet replacement (TDR) products and frequency of using fibre supplements. The scaled insights behavioural AI tool was used to infer personality traits from service users' language construction, and in doing so, examine associations with the outcomes indicated above. Findings show that service users can be profiled by personality, and this can provide a method of understanding programme outcomes. Three clusters of personality traits were identified. Despite this, there was no association between personality features and emotional wellbeing, physical activity, pain, motivation to manage diabetes, motivation to lose weight, rating of TDR products and frequency of using fibre supplements. As the self-selected sample size was limited, future research should examine the use of behavioural AI tools and personality using larger and longitudinal samples.</p>","PeriodicalId":10399,"journal":{"name":"Clinical Obesity","volume":" ","pages":"e70003"},"PeriodicalIF":2.2000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Is personality associated with the lived experience of the NHS England low calorie diet programme: A pilot study.\",\"authors\":\"Stuart W Flint, Ezra Goldberg, Mohammad Kaykanloo, Stuart Sherman, Duncan Radley, Sarah R Kingsbury, Louisa Ells\",\"doi\":\"10.1111/cob.70003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This pilot study explored the use of a novel behavioural artificial intelligence (AI) tool to examine whether personality is associated with the lived experience of the NHS England launched a low calorie diet (LCD). A cross-sectional survey was disseminated to service users to gather data on emotional wellbeing, physical activity, pain, motivation to manage diabetes, motivation to lose weight, rating of total diet replacement (TDR) products and frequency of using fibre supplements. The scaled insights behavioural AI tool was used to infer personality traits from service users' language construction, and in doing so, examine associations with the outcomes indicated above. Findings show that service users can be profiled by personality, and this can provide a method of understanding programme outcomes. Three clusters of personality traits were identified. Despite this, there was no association between personality features and emotional wellbeing, physical activity, pain, motivation to manage diabetes, motivation to lose weight, rating of TDR products and frequency of using fibre supplements. As the self-selected sample size was limited, future research should examine the use of behavioural AI tools and personality using larger and longitudinal samples.</p>\",\"PeriodicalId\":10399,\"journal\":{\"name\":\"Clinical Obesity\",\"volume\":\" \",\"pages\":\"e70003\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Obesity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/cob.70003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Obesity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/cob.70003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Is personality associated with the lived experience of the NHS England low calorie diet programme: A pilot study.
This pilot study explored the use of a novel behavioural artificial intelligence (AI) tool to examine whether personality is associated with the lived experience of the NHS England launched a low calorie diet (LCD). A cross-sectional survey was disseminated to service users to gather data on emotional wellbeing, physical activity, pain, motivation to manage diabetes, motivation to lose weight, rating of total diet replacement (TDR) products and frequency of using fibre supplements. The scaled insights behavioural AI tool was used to infer personality traits from service users' language construction, and in doing so, examine associations with the outcomes indicated above. Findings show that service users can be profiled by personality, and this can provide a method of understanding programme outcomes. Three clusters of personality traits were identified. Despite this, there was no association between personality features and emotional wellbeing, physical activity, pain, motivation to manage diabetes, motivation to lose weight, rating of TDR products and frequency of using fibre supplements. As the self-selected sample size was limited, future research should examine the use of behavioural AI tools and personality using larger and longitudinal samples.
期刊介绍:
Clinical Obesity is an international peer-reviewed journal publishing high quality translational and clinical research papers and reviews focussing on obesity and its co-morbidities. Key areas of interest are: • Patient assessment, classification, diagnosis and prognosis • Drug treatments, clinical trials and supporting research • Bariatric surgery and follow-up issues • Surgical approaches to remove body fat • Pharmacological, dietary and behavioural approaches for weight loss • Clinical physiology • Clinically relevant epidemiology • Psychological aspects of obesity • Co-morbidities • Nursing and care of patients with obesity.