Latent profile analysis (LPA) is a categorical latent variable approach that focuses on identifying latent subpopulations within a population based on a certain set of variables. LPA thus assumes that people can be typed with varying degrees of probabilities into categories that have different configural profiles of personal and/or environmental attributes. Within this article, we (a) review the existing applications of LPA within past vocational behavior research; (b) illustrate best practice procedures in a non-technical way of how to use LPA methodology, with an illustrative example of identifying different latent profiles of heavy work investment (i.e., working compulsively, working excessively, and work engagement); and (c) outline future research possibilities in vocational behavior research. By reviewing 46 studies stemming from central journals of the field, we identified seven distinct topics that have already been investigated by LPA (e.g., job and organizational attitudes and behaviors, work motivation, career-related attitudes and orientations, vocational interests). Together with showing descriptive statistics about how LPA has been conducted in past vocational behavior research, we illustrate and derive best-practice recommendations for future LPA research. The review and “how to” guide can be helpful for all researchers interested in conducting LPA studies.

潜在特征分析（LPA）是一种潜在分类变量方法，其重点是根据一组特定变量来确定总体中的潜在亚群。因此，LPA假定可以将人们以不同程度的概率归类为具有不同个人和/或环境属性的配置文件的类别。在本文中，我们（a）回顾了LPA在过去的职业行为研究中的现有应用；（b）以非技术性方式说明如何使用LPA方法的最佳实践程序，并举例说明确定繁重工作投资的不同潜在特征（即，强迫性工作，过度工作和工作投入）；（c）概述了职业行为研究的未来研究可能性。通过回顾来自该领域中央期刊的46项研究，我们确定了LPA已调查的七个不同主题（例如，工作和组织的态度和行为，工作动机，与职业相关的态度和取向，职业兴趣）。连同显示有关LPA在过去的职业行为研究中如何进行的描述性统计数据，我们说明并得出了关于未来LPA研究的最佳实践建议。这篇综述和“如何做”指南对所有有兴趣进行LPA研究的研究人员都有帮助。连同显示有关LPA在过去的职业行为研究中如何进行的描述性统计数据，我们说明并得出了关于未来LPA研究的最佳实践建议。这篇综述和“如何做”指南对所有有兴趣进行LPA研究的研究人员都有帮助。连同显示有关过去职业行为研究中LPA进行方式的描述性统计资料，我们说明并得出了关于LPA未来研究的最佳实践建议。该复习和“操作方法”指南对所有有兴趣进行LPA研究的研究人员都有帮助。