The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.
The case for motivated reasoning.
Abstract
It is proposed that motivation may affect reasoning through reliance on a biased set of cognitive processes--that is, strategies for accessing, constructing, and evaluating beliefs. The motivation to be accurate enhances use of those beliefs and strategies that are considered most appropriate, whereas the motivation to arrive at particular conclusions enhances use of those that are considered most likely to yield the desired conclusion. There is considerable evidence that people are more likely to arrive at conclusions that they want to arrive at, but their ability to do so is constrained by their ability to construct seemingly reasonable justifications for these conclusions. These ideas can account for a wide variety of research concerned with motivated reasoning.
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In the citing paper
“When people try to reason through an issue, they often work hard to find evidence that confirms their initial perspective 55-58 .”
From Predictors and consequences of intellectual humility (2022) · cites this paper as [58]
In the citing paper
“Khatun et al. (2022) and Ahsan et al. (2022) identify involuntary non-migrants in Bangladesh using retrospective, self-reported survey data, which run the risk of motivated reasoning (Kunda 1990).”
From Trapped by climate change? (In)voluntary immobility in Bangladesh (2025) · cites this paper as Kunda 1990
In the citing paper
“People may process information in a manner that is consistent with their partisan identities, prior beliefs, and motivations, a process known as motivated cognition (34–37).”
From Out-group animosity drives engagement on social media (2021) · cites this paper as [35]
In the citing paper
“The processing of false information is likely to be motivated by a confirmation bias (e.g., Hameleers et al., 2024): People are more likely to uncritically accept information when it reassures their worldviews and political attitudes, and critically scrutinize information when it does not confirm their existing worldviews (e.g., Kunda, 1990).”
From How persuasive are political cheapfakes disseminated via social media? The effects of out-of-context visual disinformation on message credibility and issue agreement (2025) · cites this paper as Kunda, 1990
In the citing paper
“Based on various theories, such as the theory of motivated reasoning, which explains that decisions are often based on pre-determined goals and desirability rather than an accurate reflection of the evidence (Kunda, 1990), researchers have identified a few individual variables that may motivate the person to believe misinformation they are exposed to.These include political orientation (Chen et al”
From Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project (2026) · cites this paper as Kunda, 1990
In the citing paper
“the reason being people's motivated reasoning (Grossman, 2014; Kunda, 1990)-the tendency to interpret reality in a self-serving way.”
From The Consequences of Participating in the Sharing Economy: A Transparency-Based Sharing Framework (2021) · cites this paper as Kunda, 1990
In the citing paper
“It is proposed that there are two distinct but coexisting human motivations that account for citizens' choice and consumption of political information: directional vs. accuracy (Kunda, 1990, or defensive vs. accuracy in Hart et al., 2009, or cognitive consistency vs. understanding in Holbert et al., 2013).”
From Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization (2020) · cites this paper as Kunda, 1990
In the citing paper
“The underlying reason for the reinforcing tendency of algorithms is that algorithms are naturally designed to operate with, not against, human tendencies, one of which is that people feel more comfortable with consistency and confirmation (Kunda, 1990).”
From Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization (2020) · cites this paper as Kunda, 1990
In the citing paper
“Yet, given the human tendency toward psychological consistency (Kunda, 1990), cognitive salience of counter-attitudinal ideas in the user mind would not be strong enough to drive routine searches online.”
From Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization (2020) · cites this paper as Kunda, 1990
In the citing paper
“The self has a powerful need to see itself as having integrity, but it must do so within the constraints of reality (Adler 2012, Kunda 1990, Pennebaker & Chung 2011, Wilson 2011).”
From The Psychology of Change: Self-Affirmation and Social Psychological Intervention (2014) · cites this paper as Kunda 1990
In the citing paper
“One kind of less epistemically rational but more epistemically committal belief in AI consciousness may manifest when AI users continue to attribute consciousness to chatbots even when strong evidence suggests otherwise, because their reasoning processes are distorted by cognitive or motivational biases.”
From Are Attributions of Consciousness to AI Chatbots Epistemically Innocent? (2026) · cites this paper as Kunda, 1990
In the citing paper
“many motivationally biased beliefs aren't yet fully insulated from counterevidence but depend on what has been called an”
From Are Attributions of Consciousness to AI Chatbots Epistemically Innocent? (2026) · cites this paper as Kunda, 1990
In the citing paper
“These mechanisms are best characterized as cognitive–motivational, insofar as they involve the goal-directed (motivational) use of information processing (cognition), as described in several classic social psychological theories88,96,97.”
From Cognitive–motivational mechanisms of political polarization in social-communicative contexts (2022) · cites this paper as [97]
In the citing paper
“It is also important to emphasize that many of these top-down influences occur automatically and without awareness (Kunda, 1990; Nickerson, 1998; Nisbett & Wilson, 1977; Wilson & Brekke, 1994).”
From Biased and biasing: the hidden bias cascade and bias snowball effects (2025) · cites this paper as Kunda, 1990
In the citing paper
“Thus, such use of reference materials causes motivation and expectations that then can bias the observations and interpretation of the actual evidence”
From Biased and biasing: the hidden bias cascade and bias snowball effects (2025) · cites this paper as Kunda, 1990
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Joel, S., Spielmann, S. S., & MacDonald, G. (2017) · Personality and Social Psychology Bulletin · doi:10.1177/0146167217702613 · Cited by 10
Metadata
- Authors
- Kunda, Z.
- Affiliations
- Princeton University (US)
- Corresponding author
- Kunda, Ziva
- Venue
- Psychological Bulletin
- Published
- 1990
- Volume
- 108
- Issue
- 3
- Pages
- 480-498
- ISSN
- 0033-2909 (ISSN-L)
- 1939-1455
- OpenAlex
- W2149893809
- Cited by
- 9,022
- References
- 100
- Citations by year
- 2026: 542 · 2025: 609 · 2024: 519 · 2023: 583 · 2022: 640 · 2021: 606 · 2020: 642 · 2019: 631 · 2018: 483 · 2017: 372 · 2016: 331 · 2015: 321 · 2014: 299 · 2013: 231 · 2012: 258
- FWCI
- 23.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Bulletin (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01mh042239-03)
- National Institute of Mental Health (1 RO1 MH42239-01A1)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Psychology › Social Psychology › Psychology of Social Influence
- Keywords
- motivated reasoning, motivation, belief evaluation, cognitive strategies, accuracy motivation, confirmation bias, justification
- MeSH terms
- Attitude, Concept Formation, Humans, Motivation, Problem Solving, Social Perception
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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