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社论综述:关注自杀问题的分析和方法学创新。

Editorial overview: Analytic and methodological innovations for suicide-focused research.

机构信息

Department of Psychology, University of Southern Mississippi, Hattiesburg, MS, USA.

Department of Clinical Psychology, Seattle Pacific University, Seattle, WA, USA.

出版信息

Suicide Life Threat Behav. 2021 Feb;51(1):5-7. doi: 10.1111/sltb.12664.

Abstract

This editorial overview provides an introduction to the Suicide and Life-Threatening Behaviors Special Issue: "Analytic and Methodological Innovations for Suicide-Focused Research." We outline several challenges faced by modern suicidologists, such as the need to integrate different analytical and methodological techniques from other fields with the unique data problems in suicide research. Therefore, the overall aim of this issue was to provide up-to-date methodological and analytical guidelines, recommendations, and considerations when conducting suicide-focused research. The articles herein present this information in an accessible way for researchers/clinicians and do not require a comprehensive background in quantitative methods. We introduce the topics covered in this special issue, which include how to conduct power analyses using simulations, work with large data sets, use experimental therapeutics, and choose covariates, as well as open science considerations, decision-making models, ordinal regression, machine learning, network analysis, and measurement considerations. Many of the topics covered in this issue provide step-by-step walkthroughs using worked examples with the accompanied code in free statistical programs (i.e., R). It is our hope that these articles provide suicidologists with valuable information and strategies that can help overcome some of the past limitations of suicide research, and improve the methodological rigor of our field.

摘要

本社论概述了《自杀与危及生命行为特刊》:“以自杀为重点的研究中的分析和方法创新”。我们概述了现代自杀研究人员面临的一些挑战,例如需要将来自其他领域的不同分析和方法技术与自杀研究中独特的数据问题相结合。因此,本专题的总体目标是为开展以自杀为重点的研究提供最新的方法学和分析指南、建议和注意事项。本文以易于研究人员/临床医生理解的方式呈现了这些信息,并且不需要对定量方法有全面的背景知识。我们介绍了本特刊涵盖的主题,包括如何使用模拟进行功效分析、处理大数据集、使用实验性治疗方法以及选择协变量,以及开放科学考虑因素、决策模型、有序回归、机器学习、网络分析和测量注意事项。本专题中的许多主题都提供了使用免费统计程序(即 R)中的示例代码进行逐步演练。我们希望这些文章为自杀研究人员提供有价值的信息和策略,帮助克服过去自杀研究的一些局限性,并提高我们领域的方法严谨性。

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