Emily E Levitt, Desmond Singh, Allan Clifton, Robert Stout, Lawrence Sweet, John F Kelly, James MacKillop
{"title":"社交网络指标对酒精使用障碍的诊断鉴别:使用高分辨率和简短评估进行初步检查。","authors":"Emily E Levitt, Desmond Singh, Allan Clifton, Robert Stout, Lawrence Sweet, John F Kelly, James MacKillop","doi":"10.1037/adb0001006","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Social network analysis (SNA) characterizes the structure and composition of a person's social relationships. Network features have been associated with alcohol consumption in observational studies, primarily of university undergraduates. No studies have investigated whether indicators from a person's social network can accurately identify the presence of alcohol use disorder (AUD), offering an indirect strategy for identifying AUD.</p><p><strong>Method: </strong>Two cross-sectional case-control designs examined the clinical utility of social network indicators for identifying individuals with AUD (cases) versus demographically matched drinkers without AUD (controls). Study 1 (<i>N</i> = 174) used high-resolution egocentric SNA assessment, whereas Study 2 (<i>N</i> = 189) used a brief assessment.</p><p><strong>Results: </strong>In Study 1, significant differences between AUD+ participants and controls were present for network alcohol severity (i.e., heavy drinking days; d = 1.23) and frequency (<i>d</i> = 0.35), but not network structural features. Network alcohol severity exhibited very good classification of AUD+ individuals versus controls (area under the curve [AUC] = 0.80), whereas network frequency did not (AUC = 0.61). In Study 2, significant differences were present for network alcohol severity (<i>d</i> = 1.02), quantity (<i>d</i> = 0.74), and frequency (<i>d</i> = 0.43), and severity exhibited good differentiation (AUC = 0.76).</p><p><strong>Conclusions: </strong>Social network indicators of alcohol involvement robustly differentiated AUD+ individuals from matched controls, and the brief assessment performed almost as well as the high-resolution assessment. These findings provide proof-of-concept for severity-related SNA indicators as promising novel clinical assessments for AUD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":48325,"journal":{"name":"Psychology of Addictive Behaviors","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnostic discrimination of social network indicators in alcohol use disorder: Initial examination using high-resolution and brief assessments.\",\"authors\":\"Emily E Levitt, Desmond Singh, Allan Clifton, Robert Stout, Lawrence Sweet, John F Kelly, James MacKillop\",\"doi\":\"10.1037/adb0001006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Social network analysis (SNA) characterizes the structure and composition of a person's social relationships. Network features have been associated with alcohol consumption in observational studies, primarily of university undergraduates. No studies have investigated whether indicators from a person's social network can accurately identify the presence of alcohol use disorder (AUD), offering an indirect strategy for identifying AUD.</p><p><strong>Method: </strong>Two cross-sectional case-control designs examined the clinical utility of social network indicators for identifying individuals with AUD (cases) versus demographically matched drinkers without AUD (controls). Study 1 (<i>N</i> = 174) used high-resolution egocentric SNA assessment, whereas Study 2 (<i>N</i> = 189) used a brief assessment.</p><p><strong>Results: </strong>In Study 1, significant differences between AUD+ participants and controls were present for network alcohol severity (i.e., heavy drinking days; d = 1.23) and frequency (<i>d</i> = 0.35), but not network structural features. Network alcohol severity exhibited very good classification of AUD+ individuals versus controls (area under the curve [AUC] = 0.80), whereas network frequency did not (AUC = 0.61). In Study 2, significant differences were present for network alcohol severity (<i>d</i> = 1.02), quantity (<i>d</i> = 0.74), and frequency (<i>d</i> = 0.43), and severity exhibited good differentiation (AUC = 0.76).</p><p><strong>Conclusions: </strong>Social network indicators of alcohol involvement robustly differentiated AUD+ individuals from matched controls, and the brief assessment performed almost as well as the high-resolution assessment. These findings provide proof-of-concept for severity-related SNA indicators as promising novel clinical assessments for AUD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>\",\"PeriodicalId\":48325,\"journal\":{\"name\":\"Psychology of Addictive Behaviors\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychology of Addictive Behaviors\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1037/adb0001006\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/4/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychology of Addictive Behaviors","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/adb0001006","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/18 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
Diagnostic discrimination of social network indicators in alcohol use disorder: Initial examination using high-resolution and brief assessments.
Objective: Social network analysis (SNA) characterizes the structure and composition of a person's social relationships. Network features have been associated with alcohol consumption in observational studies, primarily of university undergraduates. No studies have investigated whether indicators from a person's social network can accurately identify the presence of alcohol use disorder (AUD), offering an indirect strategy for identifying AUD.
Method: Two cross-sectional case-control designs examined the clinical utility of social network indicators for identifying individuals with AUD (cases) versus demographically matched drinkers without AUD (controls). Study 1 (N = 174) used high-resolution egocentric SNA assessment, whereas Study 2 (N = 189) used a brief assessment.
Results: In Study 1, significant differences between AUD+ participants and controls were present for network alcohol severity (i.e., heavy drinking days; d = 1.23) and frequency (d = 0.35), but not network structural features. Network alcohol severity exhibited very good classification of AUD+ individuals versus controls (area under the curve [AUC] = 0.80), whereas network frequency did not (AUC = 0.61). In Study 2, significant differences were present for network alcohol severity (d = 1.02), quantity (d = 0.74), and frequency (d = 0.43), and severity exhibited good differentiation (AUC = 0.76).
Conclusions: Social network indicators of alcohol involvement robustly differentiated AUD+ individuals from matched controls, and the brief assessment performed almost as well as the high-resolution assessment. These findings provide proof-of-concept for severity-related SNA indicators as promising novel clinical assessments for AUD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍:
Psychology of Addictive Behaviors publishes peer-reviewed original articles related to the psychological aspects of addictive behaviors. The journal includes articles on the following topics: - alcohol and alcoholism - drug use and abuse - eating disorders - smoking and nicotine addiction, and other excessive behaviors (e.g., gambling) Full-length research reports, literature reviews, brief reports, and comments are published.