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普遍性和代表性:互联网上物质使用行为研究的考虑因素。

Generalizability and representativeness: Considerations for internet-based research on substance use behaviors.

机构信息

Department of Biomedical Data Science.

出版信息

Exp Clin Psychopharmacol. 2022 Aug;30(4):466-477. doi: 10.1037/pha0000581.

Abstract

Substance use is frequently studied using nonprobability internet-based samples. It is difficult to evaluate the utility of these samples without a clear understanding of two key concepts: generalizability and representativeness. Part 1 of this article (a) offers a particular viewpoint on the distinctions and relations between these two concepts, (b) suggests that purposive (i.e., nonprobability) samples, when used carefully, can be used to construct valid scientific generalizations, and (c) explores some analytical consequences of sampling decisions that change sample heterogeneity. Part 2 of this article explores the overlap between internet-based sampling of substance use behaviors and the concepts discussed in Part 1. Specifically, Part 2 reviews relevant literature and presents example analyses of an internet-based cannabis use data set to highlight (a) strengths and weaknesses of internet-based sampling and (b) how unique elements of a given online platform (e.g., primary motive for visiting the platform) and the substance being studied (e.g., degree of societal stigma) might inform the types of boundaries, caveats, qualifiers, and limitations that are incorporated into a generalization crafted based on the data. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

摘要

物质使用通常采用非概率性的网络样本进行研究。如果不能清晰理解两个关键概念,即普遍性和代表性,那么就很难评估这些样本的效用。本文第一部分(a)提供了一个关于这两个概念的区别和关系的独特观点;(b)表明,当谨慎使用有目的(即非概率性)的样本时,它们可以用于构建有效的科学概括;(c)探讨了改变样本异质性的抽样决策的一些分析后果。本文第二部分探讨了网络抽样与第一部分讨论的概念之间的重叠。具体来说,第二部分回顾了相关文献,并对一个基于网络的大麻使用数据集进行了示例分析,以突出(a)基于网络的抽样的优势和劣势,以及(b)特定在线平台的独特元素(例如访问平台的主要动机)和正在研究的物质(例如,社会污名化的程度)如何为基于数据制定的概括中纳入的边界、注意事项、限定词和限制提供信息。(PsycInfo 数据库记录(c)2022 APA,保留所有权利)。

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