The competitive play of digital games known as ‘esports’ has surged in popularity over the past few decades. Millions of people nowadays participate in esports as a hobby, and many consider becoming professional esports athletes as a potential career path. However, psychological factors that may predict one's long-term success in esports are not entirely clear.

 

The current Registered Report by Martončik and colleagues (2024) offered a comprehensive test of potential predictors of long-term success in the two currently most impactful PC esports games, namely League of Legends (LoL) and Counter Strike: Global Offensive (CSGO). A wide range of predictors were examined, including native and deliberate practice, attention, intelligence, reaction time, and persistence etc. In both LoL and CSGO, deliberate practice did not meaningfully predict players' highest rank in the past 12 months, as an indicator of long-term success. Younger age predicted better performance in both titles though. Lastly, two title-specific predictors emerged: in LoL, more non-deliberate practice hours predicted better performance, while in CSGO better attention predicted better performance.

 

To explain these findings, the authors proposed the information density theory. Different games differ in the amount of knowledge that is required for achieving long-term success. For information-heavy games such as LoL, naive practice hours may be more essential for players to acquire game-relevant information via playing, compared to information-light games such as CSGO. This might also explain why deliberative practice did not meaningfully predict performance in LoL and CSGO. While this theory still needs to be further tested, the current results will be useful to individuals who are considering pursuing a professional career in esports, as well as professional and semi-professional esports teams and coaches.

 

This Stage 2 manuscript was assessed over two rounds of in-depth review. The recommenders judged the responses to the reviewers' comments were satisfactory, and that the manuscript met the Stage 2 criteria for recommendation.

 

URL to the preregistered Stage 1 protocol: https://osf.io/84zbv
 
Level of bias control achieved: Level 6. No part of the data or evidence that was used to answer the research question was generated until after IPA.
 
List of eligible PCI RR-friendly journals: 
 

• Advances in Cognitive Psychology
• Collabra: Psychology
• F1000Research
• Journal of Cognition
• Peer Community Journal
• PeerJ
• Royal Society Open Science
• Studia Psychologica
• Swiss Psychology Open
   

 
Martončik, M., Karhulahti, V.-M., Jin, Y. & Adamkovič, M. (2023). Psychological predictors of long-term esports success: A Registered Report [Stage 2]. Acceptance of Version 1.7 by Peer Community in Registered Reports. https://osf.io/b6vdf

Traditional Likert-type items are commonly used but can elicit response bias. An alternative approach, the forced-choice question, required respondents to rank order all items. Forced-choice questions boast some advantages but required advanced item response theory analysis to generate scores which are comparable across individuals and to evaluate the properties of those scales. However, there has been limited discussion of how to test differential item functioning (DIF) in these scales. In a previous study, Lee et al. (2021) proposed a method for testing DIF.

 

Here, Plantz et al. (2024) explore the implications of incorrect specification of anchors in DIF detection for forced choice items. The study proposes to use a Monte Carlo simulation which manipulates sample size, equality of sample size across groups, effect size, percentage of differentially functioning items, analysis approach, anchor set size, and percent of DIF blocks in the anchor set. This study aims to answer research questions about the type I error and power of DIF detection strategies under a variety of circumstances, both evaluating whether the results from Lee et al. (2021) generalize to misspecified models and expanding to evaluate new research questions. Results of this study will provide practical implications for DIF testing with forced-choice questions. An important limitation of the study is that it does not explore non-uniform DIF, only uniform DIF. Additionally, as with all simulation studies not all results can only apply to conditions which are simulated and so rely on the realistic selection of simulation conditions. The authors have selected conditions to match reality in circumstances where data is available, but relied on previous simulations in cases when data is not available. 

 

This Stage 1 manuscript was evaluated over two rounds of review by two reviewers with expertise in psychometrics. An additional round of review was completed by the recommender only. Based on the merits of the original submission and responsiveness of the authors to requests from the reviewers, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).​

 

URL to the preregistered Stage 1 protocol: https://osf.io/p8awx
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 

 

1. Lee, P., Joo, S.-H. & Stark, S. (2021). Detecting DIF in multidimensional forced choice measures using the Thurstonian Item Response Theory Model. Organizational Research Methods, 24, 739–771. https://doi.org/10.1177/1094428120959822

 

2. Plantz, J. W.,  Brown, A., Wright, K. & Flake, J. K. (2024). Detecting DIF in Forced-Choice Assessments: A Simulation Study Examining the Effect of Model Misspecification. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/p8awx

The rapid methodological development in digital humanities keeps opening new possibilities to better understand our cultural artifacts and, in the process, also ourselves. Some of the historically most influential works of literary human culture are the plays of Shakespeare, which continue to be read and treasured around the world. Although the social networks of Shakespeare’s plays have attracted scientific attention already more than two decades (Stiller et al. 2003), the understanding of their complexity in terms of character networks remains limited and not fully contextualized in the larger landscape of European drama.

 

In the present registered report, Thurn and colleagues (2024) apply Kolmogorov complexity analysis to investigate the social networks in 37 existing plays of Shakespeare. The authors replicate the original work by Stiller et al. (2003) and situate the findings in a larger regional context by further analyzing over 3,000 plays available in the European Drama Corpus. Ultimately, the authors explore the relationships between (Kolmogorov) complexity and the size of character networks as well as the robustness of their results in relation to possible researcher decisions in the analytic process.

 

This Stage 1 manuscript was evaluated over three rounds of in-depth review by four expert reviewers from the research fields of literature, networks, and social analysis. Based on the authors’ careful revisions and responses to the reviewers’ feedback, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/6uw27
 
Level of bias control achieved: Level 3. At least some data/evidence that will be used to the answer the research question has been previously accessed by the authors (e.g. downloaded or otherwise received), but the authors certify that they have not yet observed ANY part of the data/evidence.
 
List of eligible PCI RR-friendly journals:

 

• Collabra: Psychology
• International Review of Social Psychology
• Peer Community Journal
• PeerJ
• Royal Society Open Science
• Social Psychological Bulletin
• WiderScreen

 

 

1. Stiller, J., Nettle, D. & Dunbar, R. I. M. (2003). The small world of shakespeare’s plays. Human Nature, 14, 397-408. https://doi.org/10.1007/s12110-003-1013-1

2. Thurn, C., Sebben, S. & Kovacevic, Z. (2024) Using Shakespeare to Answer Psychological Questions: Complexity and Mental Representability of Character Networks. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/6uw27

This is an ambitious systematic review that uses a combination of quantitative and qualitative methods to make the measurement of the construct of social connection more rigorous. Social connection is a heterogeneous construct that includes aspects of structure, function and quality. Here, Paris et al. (2024) will use predefined methods to create a database of social connection measures, and will assess heterogeneity of items using human coders and ChatGPT. This database will form the basis of a second systematic review which will look at evidence for validity and measurement properties. This study will also look at the population groups and country of origin for which different measures were designed, making it possible to see how far culturally specific issues affect the content of measures in this domain.

 

The questions asked by this study are exploratory and descriptive and so the importance of pre-registration is in achieving clear criteria for how each question is addressed, rather than evidential criteria for hypothesis-testing.

 

The authors responded comprehensively to three reviewer reports. This study will provide a wealth of useful information for those studying social connection, and should serve to make the literature in this field more psychometrically robust and less fragmented.

 

URL to the preregistered Stage 1 protocol: https://osf.io/796uv
 
Level of bias control achieved: Level 3. At least some data/evidence that will be used to the answer the research question has been previously accessed by the authors (e.g. downloaded or otherwise received), but the authors certify that they have not yet observed ANY part of the data/evidence. 
 
List of eligible PCI RR-friendly journals:

 

 

 

1. Paris, B., Brickau, D., Stoianova, T., Luhmann, M., Mikton, C., Holt-Lunstad, J., Maes, A., & IJzerman, H. (2024). A systematic review of social connection inventories. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/796uv

Cognitive models ascribe a pivotal role to cognitive biases in the development and maintenance of mental disorders. For instance, attentional biases that prioritize the processing of threat-related stimuli have been suggested to be causally involved in the development and maintenance of anxiety disorders, including generalized anxiety disorder (GAD), which is marked by pathological worry. Therefore, these biases have garnered significant interest as potential diagnostic indicator and as targets for modification.

 

The idea that attention bias modification (ABM) can serve as a therapeutic intervention for GAD and other disorders was fueled by a seminal study by Hazen et al. (2009). In this study, 23 individuals experiencing high levels of worry underwent a computerized attentional retraining of threat stimuli (ARTS) or placebo control training during five training sessions. Relative to control, attention retraining was found to reduce preferential attention to threat, as well as depression and anxiety symptoms. However, as Pond et al. (2024) highlight in their review of the literature, the evidence endorsing the efficacy of ABM in alleviating anxiety disorders is still inconclusive. Moreover, some researchers contend that early positive findings might have been inflated due to demand effects.

 

Based on these considerations, Pond et al. (2024) propose a direct replication of Hazen et al. (2009) by subjecting a high-worry sample to five sessions of ARTS or placebo control. Departing from the frequentist analyses used in the original study, the authors will employ Bayesian analyses that allow more nuanced interpretation of the results, allowing consideration of evidence in support of the null hypothesis. The sampling plan will adhere to a Bayesian stopping rule, whereby the maximal sample size will be set at n=200. Furthermore, the authors extend the original study by addressing potential demand effects. For this purpose, they include a measure of phenomenological control (i.e., the ability to generate experiences align with the expectancies of a given situation) and evaluate its potential moderating impact on the attention bias training.

 

The Stage 1 manuscript was evaluated by three expert reviewers in two rounds of in-depth review. Following responses from the authors, the recommender determined that Stage 1 criteria were met and awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/5f7u9
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA. 
 
List of eligible PCI RR-friendly journals:
 

 

 

1. Hazen, R. A., Vasey, M. W., & Schmidt, N. B. (2009). Attentional retraining: A randomized clinical trial for pathological worry. Journal of Psychiatric Research, 43, 627-633. https://doi.org/10.1016/j.jpsychires.2008.07.004 

 

2. Pond, N., Meeten, F., Clarke, P., Notebaert, L., & Scott, R. B. (2024). The efficacy of attentional bias modification for anxiety: A registered replication. In principle acceptance of Version 5 by Peer Community in Registered Reports. https://osf.io/5f7u9