Concerns have been growing about the veracity of psychological research. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions, or attempt to replicate prior research, in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time-limited), efficient (in terms of re-using structures and principles for different projects), decentralized, diverse (in terms of participants and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside of the network). The PSA and other approaches to crowdsourced psychological science will advance our understanding of mental processes and behaviors by enabling rigorous research and systematically examining its generalizability.

Repeated assessments of personality states in daily diary or experience sampling studies have become a more and more common tool in the psychologist's toolbox. However, and contrary to the widely available literature on personality traits, no best practices for the development of personality state measures exist, and personality state measures have been developed in many different ways. To address this, we first define what a personality state is and discuss important components. On the basis of this, we define what a personality state measure is and suggest a general guideline for the development of such measures. Following the ABC of test construction can then guide the strategy for obtaining validity and reliability evidence: (A) What is the construct being measured? (B) What is the intended purpose of the measure? And (C) What is the targeted population of persons and situations? We then conclude with an example by developing an initial item pool for the assessment of conscientiousness personality states.

Rationale: The coronavirus disease 2019 (COVID-19) outbreak has dramatically altered people's social lives due to social restriction measures taken to control the coronavirus spread. Early on, increased loneliness has been publicly discussed as a harmful psychological side effect of these measures. Due to the serious adverse health consequences of loneliness, it is essential to take these concerns seriously and investigate them systematically to allow for evidence-based decision making. Thus far, however, high-resolution empirical evidence of such harmful side effects is rare. Methods: The present preregistered large-scale daily diary study assessed daily loneliness in 4,844 German adults between March 16 and April 12, 2020. Results and conclusion: Daily loneliness slightly increased during the first two weeks since implementing the pandemic-related measures and slightly decreased thereafter. With increasing age, daily loneliness increased more strongly over the four weeks. Moreover, daily loneliness increased more strongly for parents compared to people without children. Thus, despite some increases in loneliness in some individuals, there was no linear increase in loneliness in response to the first pandemic-related measures in the present sample.

Affect and situation perception are intertwined in any given situation, but the extent to which both predict behavior jointly and uniquely has not yet been systematically examined so far. Using two studies with experience sampling methodology (ESM), we examine how trait-like variables (Big Six, trait affect, general situation experience) and state-like variables (momentary affect, happiness, and situation perception) account for variance in self-reported behavioral states of the Big Six. In Study 1, we re-analyzed data from Sherman, Rauthmann, Brown, Serfass, and Jones (2015) and found that situation perception explained variance in self-reported behavior in logically coherent ways, but only after considering happiness as an additional predictor. These results were replicated in pre-registered Study 2, in which positive and negative affect were additionally assessed as distinct variables. Based on both studies, we conclude that personality traits, affect, and situation perception contribute uniquely to the explanation of self-reported behavior in daily life. Importantly, situation perceptions and affect do overlap, but they are neither the same nor redundant with each other. Indeed, theoretically justified and logically coherent links between situation perceptions and behavioral states remain intact once affect is controlled for, while the links not predicted by theory disappear. These results have implications for personality theories as well as appraisal theories of emotion.

Convergent correlations between traits and state aggregates from experience sampling cannot fully establish trait-state homomorphy (the extent to which the same constructs are measured). With a nomological vector correlation and lens model approach, we test how similar nomological networks of traits and state aggregates are to each other: A trait and state-aggregate capture the same construct when both show highly similar nomological associations to a common set of correlates. In large experience sampling (N ¼ 209) and life-logging studies (N ¼ 298), Extraversion, Conscientiousness, and Agreeableness tended to show more and Openness, Honesty/Humility, and Neuroticism/Emotionality tended to show less trait-state homomorphy. However, these general findings differed somewhat at the aspect level, with Neuroticism and Extraversion aspects tending to show more versus Openness and Honesty/Humility aspects tending to show less homomorphy. The proposed nomological approaches can be flexibly applied to other traits, states, and correlates.

The data presented in this manuscript were also used in the Manual of the proprietary test, The Big Five Inventory of Personality in Occupational Situations (Ziegler, 2014). Furthermore, the scales presented here have been referenced in a published book chapter (Horstmann, Rauthmann, & Sherman, accepted).

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