Schäfer Sarah K, von Boros Lisa, Göritz Anja S, Baumann Sophie, Wessa Michèle, Tüscher Oliver, Lieb Klaus, Möhring Anne
Leibniz Institute for Resilience Research, Mainz, Germany.
Department for Clinical Psychology, Psychotherapy and Psychodiagnostics, Technische Universität Braunschweig, Braunschweig, Germany.
Front Psychiatry. 2023 Jul 6;14:1195986. doi: 10.3389/fpsyt.2023.1195986. eCollection 2023.
Stress is among the leading causes for diseases. The assessment of subjectively perceived stress is essential for resilience research. While the Perceived Stress Scale (PSS) is a widely used questionnaire, a German short version of the scale is not yet available. In the current study, we developed such a short version using a machine learning approach for item reduction to facilitate the simultaneous optimization of multiple psychometric criteria.
We recruited 1,437 participants from an online panel, who completed the German long version of the PSS along with measures of mental health and resilience. An ant-colony-optimization algorithm was used to select items, taking reliability, and construct validity into account. Findings on validity were visualized by psychological network models.
We replicated a bifactor structure for the long version of the PSS and derived a two-factor German short version of the PSS with four items, the PSS-2&2. Its factors helplessness and self-efficacy showed differential associations with mental health indicators and resilience-related factors, with helplessness being mainly linked to mental distress.
The valid and economic short version of the PSS lends itself to be used in future resilience research. Our findings highlight the importance of the two-factor structure of the PSS short versions and challenge the validity of commonly used one-factor models. In cases where the general stress factor is of interest, researchers should use the longer versions of the PSS that allow for the interpretation of total scores, while the PSS-2&2 allows of an economic assessment of the PSS factors helplessness and self-efficacy.
压力是导致疾病的主要原因之一。主观感知压力的评估对于复原力研究至关重要。虽然感知压力量表（PSS）是一种广泛使用的问卷，但尚未有该量表的德语简短版本。在当前研究中，我们采用机器学习方法进行项目缩减，开发了这样一个简短版本，以促进多个心理测量标准的同时优化。
我们从一个在线样本中招募了1437名参与者，他们完成了德语版的PSS长版本以及心理健康和复原力测量。使用蚁群优化算法选择项目，同时考虑信度和结构效度。通过心理网络模型直观展示效度研究结果。
我们复制了PSS长版本的双因素结构，并推导出了一个包含四个项目的双因素德语简短版本PSS，即PSS - 2&2。其无助感和自我效能感因素与心理健康指标和复原力相关因素呈现出不同的关联，无助感主要与心理困扰相关。
有效的经济型PSS简短版本适用于未来的复原力研究。我们的研究结果突出了PSS简短版本双因素结构的重要性，并对常用的单因素模型的效度提出了挑战。在关注一般压力因素的情况下，研究人员应使用允许解释总分的PSS较长版本，而PSS - 2&2则可对PSS的无助感和自我效能感因素进行经济型评估。
