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本文引用的文献

1
Exploring the Latent Structures of Psychological Constructs in Social Development Using the Dimensional-Categorical Spectrum.使用维度-类别频谱探索社会发展中心理结构的潜在结构。
Soc Dev. 2010 Aug;19(3):470-493. doi: 10.1111/j.1467-9507.2009.00573.x.
2
Models and Strategies for Factor Mixture Analysis: An Example Concerning the Structure Underlying Psychological Disorders.因子混合分析的模型与策略:以心理障碍潜在结构为例
Struct Equ Modeling. 2013 Oct 1;20(4). doi: 10.1080/10705511.2013.824786.
3
Are the symptoms of cannabis use disorder best accounted for by dimensional, categorical, or factor mixture models? A comparison of male and female young adults.大麻使用障碍的症状是否最好通过维度、分类或因子混合模型来解释?对男女青年的比较。
Psychol Addict Behav. 2012 Mar;26(1):68-77. doi: 10.1037/a0026230. Epub 2011 Nov 14.
4
Deconstructing the age-prevalence curve of alcohol dependence: why "maturing out" is only a small piece of the puzzle.剖析酒精依赖的年龄-发病曲线:为何“成熟度”只是问题的一小部分。
J Abnorm Psychol. 2012 May;121(2):511-23. doi: 10.1037/a0026027. Epub 2011 Nov 7.
5
Addiction and dependence in DSM-V.DSM-V 中的成瘾和依赖。
Addiction. 2011 May;106(5):866-7. doi: 10.1111/j.1360-0443.2010.03144.x. Epub 2010 Oct 6.
6
Evaluating mixture modeling for clustering: recommendations and cautions.评估聚类的混合模型:建议和注意事项。
Psychol Methods. 2011 Mar;16(1):63-79. doi: 10.1037/a0022673.
7
Assessing the dimensionality of lifetime DSM-IV alcohol use disorders and a quantity-frequency alcohol use criterion in the Australian population: a factor mixture modelling approach.评估澳大利亚人群中终生 DSM-IV 酒精使用障碍的维度和酒精使用量-频率标准:因素混合建模方法。
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8
Moving toward DSM-5: the field trials.迈向《精神疾病诊断与统计手册》第五版:现场试验
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J Abnorm Psychol. 2010 Nov;119(4):650-61. doi: 10.1037/a0020116.
10
Continuous, categorical and mixture models of DSM-IV alcohol and cannabis use disorders in the Australian community.DSM-IV 酒精和大麻使用障碍的连续、分类和混合模型在澳大利亚社区。
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朝向酒精使用障碍亚型的特征描述和验证:整合消费和症状数据。

Towards the characterization and validation of alcohol use disorder subtypes: integrating consumption and symptom data.

机构信息

Center for Alcohol and Addiction Studies, Brown University, Providence, RI, USA.

出版信息

Psychol Med. 2014 Jan;44(1):143-59. doi: 10.1017/S0033291713000573. Epub 2013 Apr 3.

DOI:10.1017/S0033291713000573
PMID:23551901
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3856175/
Abstract

BACKGROUND

There is evidence that measures of alcohol consumption, dependence and abuse are valid indicators of qualitatively different subtypes of alcohol involvement yet also fall along a continuum. The present study attempts to resolve the extent to which variations in alcohol involvement reflect a difference in kind versus a difference in degree.

METHOD

Data were taken from the 2001-2002 National Epidemiologic Survey of Alcohol and Related Conditions. The sample (51% male; 72% white/non-Hispanic) included respondents reporting past 12-month drinking at both waves (wave 1: n = 33644; wave 2: n = 25186). We compared factor mixture models (FMMs), a hybrid of common factor analysis (FA) and latent class analysis (LCA), against FA and LCA models using past 12-month alcohol use disorder (AUD) criteria and five indicators of alcohol consumption reflecting frequency and heaviness of drinking.

RESULTS

Model comparison revealed that the best-fitting model at wave 1 was a one-factor four-class FMM, with classes primarily varying across dependence and consumption indices. The model was replicated using wave 2 data, and validated against AUD and dependence diagnoses. Class stability from waves 1 to 2 was moderate, with greatest agreement for the infrequent drinking class. Within-class associations in the underlying latent factor also revealed modest agreement over time.

CONCLUSIONS

There is evidence that alcohol involvement can be considered both categorical and continuous, with responses reduced to four patterns that quantitatively vary along a single dimension. Nosologists may consider hybrid approaches involving groups that vary in pattern of consumption and dependence symptomatology as well as variation of severity within group.

摘要

背景

有证据表明,饮酒量、依赖和滥用的测量是酒精摄入的不同亚类的有效指标,但也沿着一个连续体分布。本研究试图确定酒精摄入的变化在多大程度上反映了种类上的差异,而不是程度上的差异。

方法

数据来自 2001-2002 年全国酒精和相关条件流行病学调查。样本(51%为男性;72%为白种人/非西班牙裔)包括在两个波次(波次 1:n=33644;波次 2:n=25186)报告过去 12 个月饮酒的受访者。我们比较了因素混合模型(FMM),这是共同因素分析(FA)和潜在类别分析(LCA)的混合,使用过去 12 个月的酒精使用障碍(AUD)标准和五个反映饮酒频率和严重程度的饮酒指标,与 FA 和 LCA 模型进行比较。

结果

模型比较显示,在波次 1 时,最佳拟合模型是一个单因素四分类 FMM,类别主要在依赖和消费指数上有所不同。该模型使用波次 2 数据进行了复制,并针对 AUD 和依赖诊断进行了验证。从波次 1 到 2 的类别稳定性中等,最频繁饮酒类别的一致性最高。潜在因素中的类别内关联在时间上也显示出适度的一致性。

结论

有证据表明,酒精摄入既可以被视为类别性的,也可以被视为连续性的,通过四种模式来简化,这些模式沿着单一维度定量变化。分类学家可以考虑混合方法,包括在消费和依赖症状模式以及组内严重程度方面存在差异的组。