The psychology of meat-eating offers a fascinating window into moral reasoning, cognition and emotion, as well as applications in the shift toward more sustainable and ethical alternatives to meat consumption. One key observation in this field is the so-called “meat paradox” – the tendency for people to simultaneously eat meat while also caring about animals. One way to resolve this conflict and reduce cognitive dissonance is for people to separate the concept of meat from animals, mentally disengaging from the origins of meat in order to make the act of consumption more ethically acceptable. Another potential explanation is a motivated “denial of mind”, in which people believe that animals lack the mental capacity to experience suffering; therefore, eating an animal is not a harm that the animal will experience. In support of the latter hypothesis, Bastian et al (2012) found that animals judged to have greater mental capacities were also judged as less edible, and that simply reminding meat eaters that an animal was being raised for the purposes of meat consumption led to denial of its mental capacities.

 

Using a large-scale online design in 1000 participants, Jacobs et al. (2024) replicated two studies from Bastian et al. (2012): asking how the perceived mental capabilities of animals relates to both their perceived edibility and the degree of moral concern they elicit, and whether learning that an animal will be consumed influences perceptions of its mental capabilities. The original findings were successfully replicated. For study 1, attributions of mind were negatively related to animals’ edibility, positively related to negative affect towards eating animals, and positively related to moral concern for animals. For study 2, learning that an animal would be used for food led participants to attribute less mind to the animal. Overall, the results strengthen the conclusion that motivated denial of animal minds can be a mechanism for resolving the ‘meat paradox’.

 

The Stage 2 manuscript was evaluated over one round of in-depth review. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 2 criteria and awarded a positive recommendation.
 
URL to the preregistered Stage 1 protocol: https://osf.io/cru4z

 

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:

 

 

1. Bastian, B., Loughnan, S., Haslam, N., & Radke, H. R. M. (2012). Don’t mind meat? The denial of mind to animals used for human consumption. Personality and Social Psychology Bulletin, 38, 247–256. https://doi.org/10.1177/0146167211424291

 

2. Jacobs, T. P., Wang, M., Leach, S., Loong, S. H., Khanna, M., Chan, K. W., Chau, H. T., Tam, Y. Y. & Feldman, G. (2024). Revisiting the motivated denial of mind to animals used for food: Replication and extension of Bastian et al. (2012) [Stage 2]. Acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/mwyde

Comparative research is how evidence is generated to support or refute broad hypotheses (e.g., Pagel 1999). However, the foundations of such research must be solid if one is to arrive at the correct conclusions. Determining the external validity (the generalizability across situations/individuals/populations) of the building blocks of comparative data sets allows one to place appropriate caveats around the robustness of their conclusions (Steckler & McLeroy 2008).

In the current study, Alley and colleagues (2023) tackled the external validity of comparative research that relies on subjects who are either university students or participating in experiments via an online platform. They determined whether data from these two types of subjects have measurement equivalence - whether the same trait is measured in the same way across groups.

Although they use data from studies involved in the Many Labs replication project to evaluate this question, their results are of crucial importance to other comparative researchers whose data are generated from these two sources (students and online crowdsourcing). The authors show that these two types of subjects do not often have measurement equivalence, which is a warning to others to evaluate their experimental design to improve validity. They provide useful recommendations for researchers on how to to implement equivalence testing in their studies, and they facilitate the process by providing well annotated code that is openly available for others to use.

After one round of review and revision, the recommender judged that the manuscript met the Stage 2 criteria and awarded a positive recommendation.

 

Level of bias control achieved: Level 2. At least some data/evidence that was used to answer the research question had been accessed and partially observed by the authors prior to Stage 1 IPA, but the authors certify that they had not yet observed the key variables within the data that were used to answer the research question AND they took additional steps to maximise bias control and rigour.

 

 

• Advances in Methods and Practices in Psychological Science
• Collabra: Psychology
• F1000Research
• Peer Community Journal
• PeerJ
• Royal Society Open Science
• Studia Psychologica
• Swiss Psychology Open

 

 

1. Pagel, M. (1999). Inferring the historical patterns of biological evolution. Nature, 401, 877-884. https://doi.org/10.1038/44766

 

2. Steckler, A. & McLeroy, K. R. (2008). The importance of external validity. American Journal of Public Health 98, 9-10. https://doi.org/10.2105/AJPH.2007.126847

 

3. Alley L. J., Axt, J., & Flake J. K. (2023). Convenience Samples and Measurement Equivalence in Replication Research [Stage 2 Registered Report] Acceptance of Version 2 by Peer Community in Registered Reports​. https://osf.io/s5t3v

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 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

Online sports betting is becoming increasingly popular worldwide, which has raised concerns about the negative consequences it has on both individual health and public health. To prevent and reduce these negative consequences, it is important to understand how gambling-related harms arise in the context of online sports betting. 

Impulsivity has long been recognized as a risk factor for disordered gambling, yet how impulsivity may lead to gambling-related harms is not entirely clear. In the current study, Jacob and colleagues (2024) aim to examine this question using a longitudinal cross-lagged panel design. Regular online sports bettors will be invited to fill out measures of impulsivity (including impulsive choice, impulsive action, and impulsivity personality) and gambling disorder symptoms three times at three-month intervals. Player tracking data on these players' online betting behavior in these three-month intervals will then be retrieved from the online gambling provider. Combining these data provides a unique opportunity to test the hypotheses that impulsivity may lead to riskier online gambling behavior, which in turn may lead to more gambling-related problems later on. The results of the current study will offer novel insights into the causal pathways from impulsivity to disordered gambling in online sports betting, and may also inform the development of early prevention strategies to reduce gambling-related harms.

The current Stage 1 manuscript was evaluated by two reviewers and the recommender. Based on detailed responses to the reviewers' comments, 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/7wsfh
 
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:
 

References
 
1. Jacob, A., Joshanloo, M., Czernecka, R., & Kräplin, A. (2024). Impulsivity and online sports betting behavior: Untangling the causal relationship. In principle acceptance of Version 4 by Peer Community in Registered Reports. https://osf.io/7wsfh