Decisions to give to charities are affected by numerous external and internal factors. Understanding the elements influencing donation decisions is of first-order importance for science and society. On the scientific side, understanding the determinants of charity-giving contributes to the knowledge of altruistic behaviors in the presence of collective problems such as poverty, climate change, or animal welfare. On the social side, pointing out which factors affect donations can help increase prosocial behaviors and might facilitate collective actions in the case of public goods.  

Previous work has identified multiple mechanisms affecting altruistic donations to charities (Bekkers and Wiepking, 2011). Importantly, Baron and Szymanska (2011) collected empirical evidence suggesting that people prefer (i) their donations to be directly used for projects rather than organizational costs, (ii) when charities have low past costs, (iii) to diversity their donations into several NGOs, (iv) to favor charities that deal with close peers like nationals, and (v) to give voluntarily rather than through taxes. 

Here, Chan and Feldman (2024) conducted a close replication of Studies 1 to 4 of Baron and Szymanska (2011) using a large sample of online participants (four studies, overall N=1,403). In their replication, the authors found supporting evidence for the phenomena reported in the original study. In particular, people were more likely to donate to charities with lower organizational and lower past costs, to diversify their donations, and to show ingroup/nationalist preferences with larger donations to NGOs helping local over foreign children. Chan and Feldman (2024) ran additional analyses that indicated validity concerns regarding the analysis and questions that resulted in finding a preference for voluntary donations over taxation. In their added extensions that went beyond the original study, they also found that donors preferred to donate to charities whose overhead costs are paid for by other donors and unexpected evidence that making donations anonymous increased rather than decreased contributions.

The Stage 2 manuscript was evaluated over one round of in-depth review by the recommender and two expert reviewers. Following revision, 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/gmswz
 
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. Baron, J. and Szymanska, E. (2011). Heuristics and Biases in Charity. In D. M. Oppenheimer and C. Y. Olivola (Eds.), The Science of Giving: Experimental Approaches to the Study of Charity (pp. 215–235). Psychology Press. https://doi.org/10.4324/9780203865972

 

2. Bekkers, R. and Wiepking, P. (2011). A Literature Review of Empirical Studies of Philanthropy. Nonprofit and Voluntary Sector Quarterly, 40, 924–973. https://doi.org/10.1177/0899764010380927

 

3. Chan, M. and Feldman, G. (2024). Factors impacting effective altruism: Revisiting heuristics and biases in charity in a replication and extensions Registered Report of Baron and Szymanska (2011) [Stage 2]. Acceptance of Version 5 by Peer Community in Registered Reports. https://osf.io/4etkp

How do emotions interact with cognition? The last 40 years has witnessed the rise of cognitive-appraisal theories, which propose that emotions can be differentiated along an axis of cognitive dimensions such as certainty, pleasantness, attentional activity, control, anticipated effort, and responsibility (Smith and Ellsworth, 1985). Early tests of such theories focused especially on the impact of the valence – pleasantness/unpleasantness – of emotions on judgment and decision-making, finding, for instance, that negative mood induction can heighten pessimistic estimates of risk (Johnson & Tversky, 1983).

 

The Appraisal-Tendency Framework proposed by Lerner and Keltner (2000) refined cognitive-appraisal theory by proposing that specific emotions trigger a predisposition to appraise future (or hypothetical) events in line with the central appraisal dimensions that triggered the emotion, even when the emotion and the judgment are unrelated. For example, an individual who is triggered to become fearful of a heightened risk, such as nuclear war, may then exhibit heightened pessimism about risks unrelated to war. The Appraisal-Tendency Framework also predicts relationships between traits, such as fear, anger and risk-taking/risk-seeking tendencies. In an influential paper, Lerner and Keltner (2001) reported direct empirical support for the Appraisal-Tendency Framework, which aside from its influence in cognitive/affective psychology has had considerable impact in behavioural economics, moral psychology, and studies of consumer behaviour.

 

In the current study, Lu et al. (2024) replicated three key studies from Lerner and Keltner (2001) in a large online sample. Through a combination of replication and extension, the authors probed the relationship between various trait emotions (including fear, anger, happiness, and hope) and trait characteristics of risk seeking and optimistic risk assessment. The authors also examined how the ambiguity of triggering events moderates the relationship between specific emotions and risk judgments.

 

Overall, the results provide mixed support for the predictions of the Appraisal-Tendency Framework. Trait anger and trait happiness were positively associated with risk-seeking and optimistic risk estimates, while trait fear was negatively associated with optimistic risk assessment (although a reliable association between fear and risk-seeking was not observed). The original finding of Lerner and Keltner (2001) that the valence-based approach applied to risk optimism for unambiguous events was not supported. In addition, there was no reliable evidence for a positive relationship between hope and risk-seeking preference or optimistic risk estimates. The authors conclude that future research should consider a wider range of emotions to develop a more complete understanding of the link to risk-related judgment and decision-making.

 

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 therefore awarded a positive recommendation.
 
URL to the preregistered Stage 1 protocol: https://osf.io/8yu2x

 

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. Smith, C. A., & Ellsworth, P. C. (1985). Patterns of cognitive appraisal in emotion. Journal of Personality and Social Psychology, 48, 813-838. https://doi.org/10.1037/0022-3514.48.4.813

 

2. Johnson, E. J., & Tversky, A. (1983). Affect, generalization, and the perception of risk. Journal of Personality and Social Psychology, 45(1), 20–31. https://doi.org/10.1037/0022-3514.45.1.20

 

3. Lerner, J. S., & Keltner, D. (2000). Beyond valence: Toward a model of emotion-specific influences on judgment and choice. Cognition & Emotion, 14, 473-493. https://doi.org/10.1080/026999300402763 

 

4. Lerner, J. S., & Keltner, D. (2001). Fear, anger, and risk. Journal of Personality and Social Psychology, 81, 146–159. https://doi.org/10.1037/0022-3514.81.1.146

  
5. Lu, S., Efendić, E., & Feldman, G. (2024). Associations of fear, anger, happiness, and hope with risk judgments: Revisiting appraisal-tendency framework with a replication and extensions Registered Report of Lerner and Keltner (2001) [Stage 2]. Acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/xytsw

How are the thousands of existing, and yet to be created, psychological measurement instruments related, and how reliable are they? Hommel and Arslan (2024) have trained a language model--SurveyBot3000--to provide answers to these questions efficiently and without human intervention.

 

In their Stage 1 submission, the authors describe the training and pilot validation of a statistical model whose inputs are psychological measurement items or scales, and outputs are the interrelationships between the items, scales, and their reliabilities. The pilot results are promising: SurveyBot3000's predicted inter-scale correlations were extremely strongly associated with empirical correlations from existing human data.

 

The authors now plan for a further examination their model's performance and validity. They will collect novel test data across a large number of subjects, and again test the model's performance fully out of sample. Reviewers deemed these plans, and their associated planned analyses suitable. The anticipated results--along with already existing pilot results--promise a very useful methodological innovation to aid researchers in both selecting and evaluating existing measures, and developing and testing new measures.

 

The Stage 1 submission was reviewed twice by three reviewers each with expertise in the area. All reviewers identified the initial submission as timely and important, and suggested mostly editorial improvements that could be made to the Stage 1 report. After two rounds of review, the relatively minor remaining suggestions can be taken into account during preparation of the Stage 2 report.

 

URL to the preregistered Stage 1 protocol: https://osf.io/2c8hf
 
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:
 

 

 

Hommel, B. E., & Arslan, R. C. (2024). Language models accurately infer correlations between psychological items and scales from text alone. In principle acceptance of Version 4 by Peer Community in Registered Reports. https://osf.io/2c8hf

Measurement is a vital activity for all research areas, but we so often fail to provide sufficient clarity, rigor and transparency about it, undermining the validity of our studies' conclusions (Flake & Fried, 2020). This concern is of wide societal interest when applied to the domains of ideology and attitudes where measurements of both implicit and explicit attitudes are assumed to reflect the same underlying concept. The extent to which this can be accepted is undermined by mixed evidence demonstrating a lack of consensus on the extent to which relevant psychological factors similarly predict both implicit and explicit attitudes.

 

In the current study, Reid & Inbar (2023) question these assumptions through use of the Project Implicit dataset, exploring the extent to which social dominance orientation (SDO) and right wing authoritarianism (RWA) similarly predict implicit and explicit attitudes. This work was ideally suited for publication through the Registered Reports format because whilst it may have been expected that relationships between SDO/RWA are similar in effect size across measures of both implicit and explicit attitude (because they tap into the same underlying attitude), there was great scope to acknowledge a more complex set of findings which may not be immediately interpretable or coherent.

 

As expected, the results were not completely unambiguous, but the mostly consistent relationships between implicit attitudes and RWA/SDO provided evidence towards both implicit and explict measures capturing the same underlying construct. These results also provide a useful step forward in our discussion of measurement in this domain, acknowledging the complexity of the tradeoff between reliability and specificity.

 

The Stage 2 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 2 criteria and awarded a positive recommendation. 

 

URL to the preregistered Stage 1 protocol: https://osf.io/zv4jw
 
Level of bias control achieved: Level 5. All of the data or evidence that was used to answer the research question existed before the research commenced but was inaccessible to the authors and thus unobservable prior to IPA.
 
List of eligible PCI-RR-friendly journals:
 

References
 
1. Flake, J. K. & Fried, E. I. (2020). Measurement schmeasurement: Questionable measurement practices and how to avoid them. Advances in Methods and Practices in Psychological Science, 3, 456-465. https://doi.org/10.1177/2515245920952393
 
2. Reid, J. & Inbar, Y. (2024). Implicit Ideologies: Do Right-Wing Authoritarianism and Social Dominance Orientation Predict Implicit Attitudes? [Stage 2]. Acceptance of Version 6 by Peer Community in Registered Reports. https://doi.org/10.31234/osf.io/8udps

This recommendation concerns the plan of two studies that are intended to be conducted simultaneously, using the same data collection approach, and to result in two manuscripts that will be submitted for assessment at Stage 2. The Stage 1 manuscript containing these protocols was submitted via the programmatic track.

 

Protocol 1 concerns “Open Scholarship and Feedback in Applied Research: A Qualitative Registered Report”. With this study, the authors aim to explore how applied researchers integrate feedback processes into their work, in relation to transparency and rigor in particular. They will investigate whether their sample are aware of and use feedback mechanisms from the open science movement, such as registered reports, which makes this study nicely metascientific. Through interviews with 50 applied researchers from various fields, the study will examine current feedback practices. The authors intend to use the findings of this first study to inform recommendations on how open science practices can be incorporated into research workflows.

 

Protocol 2 concerns “Understanding the Role of Climate Change in Applied Research: A Qualitative Registered Report”. This study aims to explore how applied researchers address climate change in their work, including the ways their practices are influenced by and respond to climate challenges. It addresses how their approaches may evolve, and they plan to look into the barriers and opportunities climate change presents in practice. Interviews with 50 applied researchers will be analysed to help understand these dynamics. The authors aim to provide recommendations to help applied researchers and their employers adjust their priorities to align with the urgency of climate action. One reviewer did not comment on this second protocol, as the content was outside of their own research area. Although I would have found a reviewer who specializes in this area directly ideally, I found I could still rely on the other two reviewers and my own knowledge to assess this protocol.
 
General comments: As I mentioned in my initial assessment text, these studies were well planned from the get-go and the protocol nicely articulated those plans. The use of different colour highlighting clearly helped the reviewers target different elements of the protocol and give direct feedback on specific parts. It also helped prevent me from getting lost in all the details! Well done, once again, to the authors for making the distinction between the two studies so clear. I was also pleased at how well they balanced the information between the two protocols – this made it easier to see if there were deficiencies in either one somehow. Finally, I loved that reflexivity was considered by the authors. One suggestion by me is that the authors might consider providing a collective positionality statement to go with the trainees’ reflexivity statements (if this is already in the plan and I missed it, please forgive the oversight!) in the final studies, even if as part of an appendix. This is because the open science movement and climate change can both be controversial, and because of the nature of the qualitative approach I would like to understand a little of the stance the group takes towards these issues collectively if the authors think it’s appropriate. I understand that with a big group that might be difficult or impossible, but if it is possible I would like to see it. I would also like to see initials used in the manuscripts to indicate who was responsible for what analysis elements where possible. This allows for accountability and to attribute interpretation to specific individuals involved in the data analysis. Alternatively, individuals can be attributed in a statement at the end of each manuscript to serve the same purpose and be less awkward in the text. If this won't work for some reason, please motivate this decision. 

 

The three reviewers that took the time to go through the reports nevertheless had useful comments, most of which would have contributed to strengthening the plan and minimizing problematic bias later on. The authors took these comments seriously, and thoughtfully (cheerfully even) responded to each. In my estimation, each of the suggestions of the reviewers were satisfied by the authors’ response to reviews letter. Other than my earlier comment about the positionality statement, I have no further comments for the Stage 1 protocol, and I wish the authors all the best with running the studies and writing up Stage 2 for each.

 

URL to the preregistered Stage 1 protocol: https://osf.io/jdh32
 
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:
 

 

 

Evans, T. R. et al. (2024). Open Scholarship and Feedback in Applied Research/Understanding the Role of Climate Change in Applied Research: A Qualitative Registered Report. In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/jdh32