Screen recordings for the preregistration of the Registered Report Protocol: Survey on attitudes and experiences regarding preregistration in psychological research

Background: Preregistration, the open science practice of specifying and registering details of a planned study prior to knowing the data, increases the transparency and reproducibility of research. Large-scale replication attempts for psychological results yielded shockingly low success rates and contributed to an increasing demand for open science practices among psychologists. However, preregistering one’s studies is still not the norm in the field. Here, we propose a study to explore possible reasons for this discrepancy. Methods: In a mixed-methods approach, an online survey will be conducted, assessing attitudes, motivations, and perceived obstacles with respect to preregistration. Participants will be psychological researchers that will be recruited by scanning research articles on Web of Science, PubMed, PSYNDEX, and PsycInfo, and preregistrations on OSF Registries (targeted sample size: N = 296). Based on the theory of planned behavior, we predict that positive attitudes (moderated by the perceived importance of preregistration) as well as a favorable subjective norm and higher perceived behavioral control positively influence researchers’ intention to preregister (hypothesis 1). Furthermore, we expect an influence of research experience on attitudes and perceived motivations and obstacles regarding preregistration (hypothesis 2). We will analyze these hypotheses with multiple regression models, and will include preregistration experience as control variable. This is a preregistration for the described study. The Registerd Report Protocol is currently under review.

Pilot data as well as meta-data and analysis scripts are provided.

Code for analyzing A) all pilot data and B) only complete datasets. Furthermore, assumptions for the used statistical models are tested.

S6 Script. Preprocessing script (preliminary). This R script contains all steps of preprocessing. The hereby processed data will be used for the assumption tests as well as for the descriptive reports and hypotheses tests. If necessary, small changes may be made to enable correct functioning (when variables have been inserted). S7 Script. Assumption testing script (preliminary). This R script will be used for testing the assumptions of the statistical models used to test hypotheses 1 and 2. If necessary, small changes may be made to enable correct functioning (when variables have been inserted). S8 Script. Analysis script (preliminary). This script will be used to conduct the descriptive reports as well as the hypotheses tests of the survey. If necessary, small changes may be made to enable correct functioning (when variables have been inserted). Furthermore, analyses might be added if alternative approaches need to be used (due to assumption violation).

S1 Text. Power analyses. Power analyses for both hypotheses are presented here. For hypothesis 1, power analyses were performed for the entire model as well as for the individual predictors. S2 Text. Data collection procedure. The data collection procedure that is displayed in Fig 2 is further specified. Particularly, the specific procedures for collecting contact addresses as well as for inviting participants are described. S3 Table. Survey items. The items of the survey are presented. If they were derived from other studies, the original items as well as references are given.