Everyday decisions can often be biased by how different options are presented and which choices were made previously, over and above whichever option is rationally preferable. Two such major biases in judgment and decision-masking are status quo bias and the default effect. The status quo bias reflects a tendency for people to choose an option that has already been implemented or represents the current state of affairs (for instance, choosing to remain with a current energy supplier rather than switching to a different one, even when the current supplier provides less value for money), while the default effect is a bias toward taking a course of action that would occur automatically in the absence of an active choice (such as the pre-selected energy supplier in questionnaire). Status quo bias and default effects can overlap or diverge: the status quo option will often be the same as the default, while on other occasions the default option in a choice set will be determined by other factors and differ from the option that was already implemented.

 

In the current study, Yam and Feldman (2023) propose a replication and extension of an influential study by Dinner et al. (2011) that purported to examine default effects but, arguably, actually studied its nearby cousin, status quo bias. Using a large online sample, the authors will independently test for the existence of both status quo bias and the default effect, before then asking whether (and if so how) status quo bias and default effects interact and how they are related to several potential explanatory variables, including perceived effort (which may be lower for the status quo or default) and endorsements (whether through direct recommendations or indirectly through perceived norms). The authors also build in additional manipulation checks and comprehension checks, in addition to exploratory analyses examining (among other variables), the political orientation of participants.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. 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/ep3jh
 
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:
 

References
 

1. Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011). Partitioning default effects: Why people choose not to choose. Journal of Experimental Psychology: Applied, 17, 332– 341. https://doi.org/10.1037/a0024354

2. Yam, M. L. M.  & Feldman, G. (2023). Reference points and decision-making: Impact of status quo and defaults in a conceptual replication and extensions Registered Report of Dinner et al. (2011), in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/ep3jh

Emotion is a well-established mediator of decision-making, including prospective economic decisions, but does it affect the way we respond economically to loss? According to classic economic theories, when an object is lost and cannot be recovered, our emotional attachment to that object should be irrelevant for decisions such as choosing whether to claim insurance or compensation. Intriguingly, however, this does not appear to be the case: in a series of experiments, Hsee and Kunreuther (2000) found that when people have higher affection towards an object, they are more sensitive to its loss and are more willing to claim compensation or purchase insurance for the object. They explained these findings according to an influential “consolation hypothesis” in which people see insurance compensation as means to mitigate against the emotional distress associated with property loss.

 

Using a large online sample (N=1000), Law and Feldman (2023) propose to replicate four of six studies from Hsee and Kunreuther (2000), each asking (primarily) whether people with higher affection towards an object are more willing to claim compensation or purchase insurance for that object. In each experiment, participants are randomly assigned to either a high affection group or a low affection group and then given a scenario in which the level of affection to an object is correspondingly manipulated while the monetary value is held constant. For example, for high affection: “You liked the now-damaged painting very much and you fell in love with it at first sight. Although you paid only $100, it was worth a lot more to you”, and for low affection: “You were not particularly crazy about the now-damaged painting. You paid $100 for it, and that’s about how much you think it was worth.” A range of dependent measures are then collected, including the maximum hours participants would be willing to spend driving to claim compensation, the maximum amount participants would be willing to pay for insurance, and how likely participants would be to claim compensation or purchase insurance. As part of the replication, the authors have also built in manipulation checks to confirm that the scenarios influenced participants' (imagined) level of affection for the object, and a range of exploratory analyses.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. 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/b7y5z
 
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:
 

 

References
 

1. Hsee, C. K., & Kunreuther, H. C. (2000). The affection effect in insurance decisions. Journal of Risk and Uncertainty, 20, 141-159. https://doi.org/10.1023/A:1007876907268

2. Law, Y. Y. & Feldman, G. (2023). Revisiting the impact of affection on insurance purchase and claim decision-making: Replication and extensions Registered Report of Hsee and Kunreuther (2000), in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/b7y5z

Compared to the wealth of debate surrounding replicability and transparency, relatively little attention has been paid to the issue of generalisability – the extent to which research findings hold across different samples, cultures, and other parameters. Existing research suggests that researchers in psychology are prone to generalisation bias, relying on narrow samples (e.g. drawn predominantly from US or European undergraduate samples) to draw broad conclusions about the mind and behaviour. While recent attempts to address generalisability concerns have been made – such as journals requiring explicit statements acknowledging constraints on generality – addressing this bias at root, and developing truly generalisable methods and results, requires a deeper understanding of how researchers perceive generalisability in the first place.

 

In the current study, Schmidt et al. (2023) tackle the issue of cross-cultural generalisability using four large-scale international studies that are being conducted as part of the Psychological Science Accelerator (PSA) – a globally distributed network of researchers in psychology that coordinates crowdsourced research projects across six continents. Specifically, participants (who will be PSA research members) will estimate the probability that an expected focal effect will be observed both overall and within regional subsamples of the PSA studies. They will also predict the size of these focal effects overall and by region.

 

Using this methodology, the authors plan to ask two main questions: first whether researchers can accurately predict the generalisability of psychological phenomena in upcoming studies, and second whether certain researcher characteristics (including various measures of expertise, experience, and demographics) are associated with the accuracy of generalisability predictions. Based on previous evidence that scientists can successfully predict the outcomes of research studies, the authors expect to observe a positive association between predicted and actual outcomes and effect sizes. In secondary analyses, the authors will also test if researchers can predict when variables that capture relevant cultural differences will moderate the focal effects – if so, this would suggest that at least some researchers have a deeper understanding as to why the effects generalise (or not) across cultural contexts.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. 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/vwqsa (under temporary private embargo)
 
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. Schmidt, K., Silverstein, P. & Chartier, C. R. (2023). Registered Report: Researcher Predictions of Effect Generalizability Across Global Samples. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/vwqsa

What determines whether groups of people can come up with ideas that are both original and useful? Since the 1960s, this question has been intensively studied with the help of more or less structured group creativity activities such as brainstorming or creative problem solving, with subsequent rating of the generated ideas.

In this line of research, personal factors—such as personality traits, and other interindividual differences in emotion and cognition—have received substantial attention as potential correlates of creative outcomes of group activities. This has spawned a sprawling literature that, to date, has not yet been synthesized. Thus, empirical findings in this literature, which are also sometimes contradictory, have not yet been well-integrated.

In the present study, Fillon et al. (2022) conducted the first meta-analysis of correlations between personal factors and group creativity outcomes. The authors searched and synthesized the existing published literature according to predetermined criteria to (1) assess the overall relationship between a broad list of personal factors and creativity outcomes in group settings and (2) explore potential moderators of these relationships. 

In total, 11 studies could be included in the meta-analysis. They provided weak support for a positive correlation between self-efficacy and the three investigated group creative outcomes, number of ideas, originality of ideas, and usefulness of ideas. With respect to moderators, many of the planned analyses could not be conducted due to the low number of studies. The only finding that arose was weak evidence for the idea that time constraint moderates associations: relationships between personal factors and group creativity outcomes were slightly stronger for tasks limited to 20 minutes rather than 10 minutes. Statistical power overall was low across studies.

The authors conclude their meta-analysis with the observation that the available data on the topic are very limited. They suggest that to improve our knowledge of the topic, future studies should adhere to standardized creativity methods and protocols and implement expert ratings of creativity. They also call for increasing the availability of raw data in this field of study to improve the accumulation of knowledge about links between personal factors and the creative performance of groups.

The Stage 2 manuscript was evaluated over one round of in-depth review provided by the recommender and Chris Chambers, as the original reviewers were no longer available. Based on additional changes to the manuscript, 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/nybg6
 
Level of bias control achieved: Level 3. At least some data/evidence that was used to answer the research question had been previously accessed by the authors (e.g. downloaded or otherwise received), but the authors certified that had not yet observed ANY part of the data/evidence prior to IPA.
 
List of eligible PCI RR-friendly journals:
 

The N2pc is a lateralised ERP component that is often interpreted as a marker of attentional allocation, so much so that it is frequently used a tool in the attention literature for inferring that a stimulus was attentionally processed. This interpretation of N2pc can be traced back to the seminal work of Eimer (1996), which has been conceptually replicated many times but has never been replicated directly.

 

This registered direct replication by Constant et al. (2023) forms part of a larger series of large-scale, multi-lab replications of highly influential EEG papers by the #EEGManyLabs project (Pavlov et al., 2021). Seven labs (with the potential for more to sign up later), will conduct high-powered replications of the critical Experiment 2 of Eimer (1996), where in the crucial conditions, participants discriminate a target letter (M vs W) or colour (blue vs green) in the presence of a distractor. Using four preprocessing pipelines, including the original, the authors will test whether the N2pc is observed over parieto-occipital electrodes contralateral to target presentation.  

 

The Stage 1 manuscript was evaluated over one round of in-depth review and one additional round of minor corrections. 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).

 

 

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 (so-called “primary RR”)

 

 

 

 

1. Constant, M., Mandal, A., Asanowicz, D., Yamaguchi, M., Gillmeister, H., Kerzel, D., Luque, D., Pesciarelli, F., Fehr, T., Mushtaq, F., Pavlov, Y. G. & Liesefeld, H. R. (2023). A multilab investigation into the N2pc as an indicator of attentional selectivity: Direct replication of Eimer (1996), in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/dw68r

 

2. Eimer, M. (1996). The N2pc component as an indicator of attentional selectivity. Electroencephalography and Clinical Neurophysiology, 99, 225-234. https://doi.org/10.1016/0013-4694(96)95711-9

 

3. Pavlov, Y. G., Adamian, N., Appelhoff, S., Arvaneh, M., Benwell, C. S., Beste, C., ... & Mushtaq, F. (2021). #EEGManyLabs: Investigating the replicability of influential EEG experiments. Cortex, 144, 213-229. https://doi.org/10.1016/j.cortex.2021.03.013