Browse 12 peer-reviewed papers published in 2026. Research studies powered by Prolific's participant recruitment platform.
This page lists 12 peer-reviewed papers published in 2026 in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
-
Authors: L Qiu, F Sha, K Allen, Y Kim, T Linzen, S van Steenkiste
Year: 2026
Published in: Nature …, 2026 - nature.com
Institution: Meta, Google DeepMind, Massachusetts Institute of Technology, Google Research, Google
Research Area: Probabilistic reasoning, Bayesian cognition, Neural language models, Reasoning, AI Evaluations
Discipline: Machine learning, Artificial intelligence
This paper sits at the intersection of machine learning and computational cognitive science, showing that large language models can acquire generalized probabilistic reasoning by being trained to imitate Bayesian belief updating rather than relying on prompting or heuristics.
Citations: 8
-
Authors: K Rudnicki, O Borowiecki, K Poels, B Beersma
Year: 2026
Published in: Evolution and Human …, 2026 - Elsevier
Institution: University of Antwerp, University of Bialystok, VU University, Emory University
Research Area: Personality psychology, Social cognition, Cognitive neuroscience
Discipline: Evolutionary psychology, human behavioral ecology
In a preregistered study, psychopathy (more than the other Dark Triad traits) is linked to worse cognitive empathy and greater dehumanization, and this empathy–psychopathy link is especially strong among people who are less sensitive at detecting agency in others.
-
Authors: H Zhu, J Chen, N Liu
Year: 2026
Published in: International Journal of Hospitality Management, 2026 - Elsevier
Institution: Sun Yat-Sen University
Research Area: Leadership studies, Organizational psychology, hospitality research, Attachment theory
Discipline: Organizational Behavior, Management
Leader secure-base support improves hospitality employees’ service performance by boosting work engagement, but this benefit is weakened when employees experience high role ambiguity or role conflict.
-
Authors: JW Berge, LIO Berge, W Chiu, I Kolstad
Year: 2026
Published in: The Journal of Development Studies, 2026•Taylor & Francis
Institution: Norwegian School of Economics
Effective altruism information treatment showed no effect on donations to advocacy organisations but increased support for international-focused NGOs, particularly among donors with less universalistic preferences and low trust in NGOs.
Methods: Randomised online discrete choice experiment with pre-registration and incentivised donation measurement.
Key Findings: Impact of effective altruism information treatment on donor behaviour and NGO support preferences.
DOI: https://doi.org/10.1080/00220388.2025.2601583
-
Authors: C Yuan, B Ma, Z Zhang, B Prenkaj, F Kreuter, G Kasneci
Year: 2026
Published in: arXiv preprint arXiv:2601.08634, 2026•arxiv.org
Institution: Munich Center for Machine Learning, LMU Munich, Technical University of Munich
Research Area: Artificial Intelligence, AI Ethics, AI Alignment, Political Science, Computational Social Science
Discipline: Computer Science, Natural Language Processing (NLP)
This paper examines how large language models’ (LLMs) political outputs shift when you explicitly prime them with different moral values. Instead of just assigning fake personas (like “pretend to be liberal”), the authors condition models to endorse or reject specific moral values (e.g., utilitarianism, fairness, authority). They then measure how those moral primes move the models’ positions in...
DOI: https://doi.org/10.48550/arXiv.2601.08634
-
Authors: L Dai, Z Wang, L Chen, J Jin
Year: 2026
Published in: 2026•scholarspace.manoa.hawaii.edu
Institution: Shanghai International Studies University
Research Area: Socio-Economic Impacts of AI, Algorithmic Systems
Discipline: Computer Science, Artificial Intelligence
AI errors lead to broader negative generalizations about other AI systems compared to human errors, largely due to perceptions of AI's inflexibility and inability to learn from mistakes.
Methods: Conducted four one-factor experiments across distinct contexts to compare human responses to AI errors and human errors.
Key Findings: Generalization of error perceptions from one AI system to others, and psychological mechanisms driving this process.
-
Authors: J He, C Calluso, C Donato, R Thouvarecq
Year: 2026
Published in: … - Journal of Retailing and …, 2026 - Elsevier
Institution: Luiss University, Roma Tre University, Univ Rouen Normandie, Le Mans Université
Research Area: Message framing, Psychological reactance, Self-image traits
Discipline: Consumer behavior
This paper looks at why some people get annoyed / push back (“psychological reactance”) when online grocery sites show healthy-eating PSAs, especially when the PSA is framed as a warning (“If you don’t eat well, you’ll suffer”) vs a benefit (“If you eat well, you’ll gain”).
-
Authors: M Raj, JM Berg, R Seamans
Year: 2026
Published in: Journal of Experimental Psychology …, 2026 - psycnet.apa.org
Institution: New York University, University of Michigan, Wharton
Research Area: Disclosure psychology, Biases in human–machine evaluation, AI Biases
Discipline: Experimental psychology
This paper sits at the intersection of experimental psychology, social cognition, and consumer judgment, examining how AI disclosure triggers persistent authenticity-based bias against creative work, revealing a robust form of algorithmic aversion in symbolic and expressive domains.
DOI: https://doi.org/10.1037/xge0001889
-
Authors: X Yang, N Xi, J Hamari
Year: 2026
Published in: 2026 - scholarspace.manoa.hawaii.edu
Institution: Tampere University
Research Area: NFT, Gamification, Virtual economies
Discipline: Human–Computer Interaction (HCI), Consumer behavior, Behavioral psychology
Using a Prolific survey of 805 people, the paper shows that Big Five personality traits predict why people “love vs. hate” NFT art—with agreeableness and conscientiousness linked to higher perceived value across most dimensions, and neuroticism linked to more skepticism (especially about transparency).
-
Authors: H Mohseni, T Kujala, J Silvennoinen
Year: 2026
Published in: SPRINGER
Institution: University of Jyväskylä
Research Area: Migration studies, Social indicators, Psychometrics, Quantitative social science methods
Discipline: Social sciences
Developed and validated a multidimensional place-belongingness scale to assess immigrants' sense of belonging to geographic locations, identifying four factors: feeling at home, accepted, empowered, and secure.
Methods: Survey data from 270 immigrants worldwide analyzed using exploratory factor analysis.
Key Findings: The subjective sense of place-belongingness, decomposed into four factors: feeling at home, feeling accepted, feeling empowered, and feeling secure.
Sample Size: 270
-
Authors: S Assecondi
Year: 2026
Published in: SPRINGER
Institution: University of Trento
Research Area: Geropsychology, Cognitive intervention research, Psycholinguistics, Neuropsychology
Discipline: Psychology, Cognitive Science
Working memory training shows modest improvements in reading comprehension for younger adults but not older adults, highlighting the need for ecologically valid measures in cognitive training programs.
Methods: Participants underwent a 5-day cognitive training program targeting visuo-spatial working memory to evaluate effects on reading comprehension as a proxy for everyday functions.
Key Findings: The relationship between visuo-spatial working memory improvements and reading comprehension performance across age groups.
Sample Size: 175
-
Authors: N Petrova, A Gordon, E Blindow
Year: 2026
Published in: Open review
Institution: Prolific
Research Area: Human-centered AI evaluation, Bayesian statistics, Responsible AI, AI alignment, LLM Evaluation
Discipline: Machine Learning, Artificial Intelligence
The study introduces HUMAINE, a multidimensional evaluation framework for LLMs, revealing demographic-specific preference variations and ranking google/gemini-2.5-pro as the top-performing model with a posterior probability of 95.6%.
Methods: Multi-turn naturalistic conversations analyzed using a hierarchical Bayesian Bradley-Terry-Davidson model with post-stratification to census data, stratified across 22 demographic groups.
Key Findings: Performance of 28 LLMs across five human-centric dimensions, accounting for demographic-specific preferences.
Sample Size: 23404