No Evidence of Experimenter Demand Effects in Three Online Psychology Experiments

Abstract

Experimenter demand effects occur when participants alter their behavior to align with perceived study hypotheses, threatening internal validity. Concern about demand effects is pervasive in psychology. Experimenter demand may be especially acute in studies relying on experienced participants recruited online (e.g., via Prolific), who may readily guess hypotheses, or using common paradigms (e.g., vignette studies and interventions) where study goals are transparent. We conducted three preregistered experiments (N = 2,254) examining whether explicit demand cues influence online participants’ behavior across three paradigms commonly used in psychology: a dictator game, replicating prior work on demand effects (Experiment 1); a moral dilemma vignette (Experiment 2); and an intervention on group attitudes (Experiment 3). We randomly assigned participants on Prolific to receive information about the study’s hypothesis or to a no-information control. As expected, we find that receiving such information significantly shifts participants’ beliefs about the study’s hypothesis, creating an experimenter demand. Yet we find no evidence that learning any study’s hypothesis alters participants’ behavior, judgments, or attitudes, suggesting that demand effects may be elusive in online samples. These findings offer important insights for the design and interpretation of modern psychology experiments.

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Citations
Research
Paper Only

Study specs

Three preregistered experiments on Prolific tested the impact of explicit demand cues on participant behavior using a dictator game, a moral dilemma vignette, and a group attitude intervention. Participants were randomly assigned to receive information about the study hypothesis or no information.

Sample Size
N=2,254
Study Type
Experimental Study
Year
2025
Human Data Platform
Prolific

Measured Outcomes

Whether explicit demand cues influence behavior, judgments, or attitudes in online psychology studies.

Peer Review & Critical Discussion

3 threads

Potential Selection Bias in 2023 Cohort

DSJDr. Sarah J.
Verified PhD Candidate
12 replies

The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.

2 hours ago

Non-naive Participants Issue

MCM. Chen (OpenAI)
Data Scientist
8 replies

I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.

5 hours ago

RLHF Applicability to This Study Design

PRWProf. R. Williams
Verified Researcher
15 replies

The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.

1 day ago

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