You will be provided with a research report. The body of the report will contain some citations to references.

Citations in the main text may appear in the following forms:
1. A segment of text + space + number, for example: "Li Qiang constructed a socioeconomic status index (SES) based on income, education, and occupation, dividing society into 7 levels 15"
2. A segment of text + [number], for example: "Li Qiang constructed a socioeconomic status index (SES) based on income, education, and occupation, dividing society into 7 levels[15]"
3. A segment of text + [number†(some line numbers, etc.)], for example: "Li Qiang constructed a socioeconomic status index (SES) based on income, education, and occupation, dividing society into 7 levels[15†L10][5L23][7†summary]"
4. [Citation Source](Citation Link), for example: "According to [ChinaFile: A Guide to Social Class in Modern China](https://www.chinafile.com/reporting-opinion/media/guide-social-class-modern-china)'s classification, Chinese society can be divided into nine strata"

Please identify **all** instances where references are cited in the main text, and extract (fact, ref_idx, url) triplets. When extracting, pay attention to the following:
1. Since these facts will need to be verified later, you may need to look for some context before and after the citation to ensure that the fact is complete and understandable, rather than just a simple phrase or short expression.
2. If a fact cites multiple references, then it should correspond to two triplets: (fact, ref_idx_1, url_1) and (fact, ref_idx_2, url_2).
3. For the third form of citation (i.e., where the citation source and link appear directly in the text), the ref_idx should be uniformly set to 0.
4. If the main text does not specify the exact location of the citation (for example, only the reference list is listed at the end of the article, without specifying the citation point in the text), please return an empty list.

You should return a JSON list format, where each item in the list is a triplet, for example:
[
    {
        "fact": "Text segment from the original document. Note that Chinese quotation marks should use full-width marks. And add a single backslash before the English quotation mark to make it a readable for python json module.",
        "ref_idx": "The index of the cited reference in the reference list for this text segment.",
        "url": "The URL of the cited reference for this text segment (extracted from the reference list at the end of the research report or from the parentheses at the citation point)."
    }
]

Here is the main text of the research report:
## Executive Summary

Need for cognitive closure (NFC) is the desire to be certain about an issue and to avoid ambiguity, with high-closure individuals tending to “seize” on need-satisfying information and “freeze” on it to preserve certainty [4]. For misinformation acceptance—here spanning conspiracy narratives, fake-news headlines, post-event eyewitness misinformation, and repetition-based truth judgments [1][8][13][14]—the evidence supports a conditional, modest role rather than a stable main effect [1][2][4][13].

NFC can increase conspiracy endorsement when conspiratorial explanations are salient and events lack clear official explanations, but in one experiment the NFCC–conspiracy association reversed direction when an official, non-conspiratorial explanation was available, indicating a cue-dependent statistical interaction rather than a causal reversal of the closure motive itself [1]. In a German representative panel (N = 2,883), NFC predicted COVID-19 conspiracy belief only weakly (z-standardized coefficient 0.08), while pre-pandemic political trust and concurrent crisis trust were much stronger negative predictors (−0.33 and −0.51), and trust did not moderate the NFC–conspiracy association [4].

Experimentally lowering closure through accountability reduced belief-consistent assimilation of evidence, suggesting situational accountability can alter closure-driven processing [2]. Repetition-driven acceptance appears largely closure-independent: across seven studies, the illusory truth effect was robust to need for cognitive closure [13].

Thus, NFC may increase acceptance when a simple explanation is accessible [1], but evidence that trusted explanations or accuracy-related cues override it is mixed or indirect: accountability can reduce closure-driven assimilation [2], high involvement can promote systematic processing [11], while institutional trust did not moderate NFC’s association with conspiracy belief in the German panel [4].

## Definition, measurement, and construct boundaries

NFC/NFCC/NCC is defined as a desire to be certain about an issue and to avoid ambiguity; individuals high in NFC are characterized by a tendency to accept need-satisfying information quickly (“seizing”) and to maintain a judgment that has been reached to preserve closure (“freezing”) [4]. It is treated as a cognitive-motivational dynamic rather than a static trait, and it can be situationally heightened by time constraints or cognitive load or lowered by accountability [2][4]. The standard self-report instrument is the Need for Closure Scale; the 15-item short version includes uncertainty intolerance, preference for order and predictability, urgency (“dying to reach a solution very quickly”), and closed-mindedness, with higher total scores indicating greater closure [6]. The scale’s scoring note interprets totals up to 30 as low and 75–90 as high [6]. In the reviewed studies, reliability varied: the NFCS-5 had Cronbach’s α = 0.67 in a German survey [4], the NFCS-15 had α = 0.87 in a COVID-19 sample [5], and the Hungarian 15-item version had α = 0.84 in a fake-news panel [14]. A construct warning is needed because some “NFC” findings concern Need for Cognition, the preference for effortful elaboration, not need for closure; these are distinct constructs and should not be merged [12].

## Empirical direction: a small, cue-dependent trait effect

The empirical pattern is not a simple positive NFC–misinformation relationship [1][2][4][5][13][14]. Table 1 summarizes the key direct tests.

| Evidence | Finding under stated conditions | Implication for NFC |
| --- | --- | --- |
| Conspiracy experiments [1] | NFCC positively predicted endorsement of a refugee-crisis conspiracy and a plane-crash conspiracy when conspiratorial explanations were salient; the NFCC–conspiracy link reversed when the plane crash had an official, non-conspiratorial explanation [1]. | NFC amplifies whichever explanation is situationally accessible, not falsehood per se [1]. |
| Small conspiracy studies (N = 30 and N = 86) [2] | Study 1 found no relationship between NFCC and conspiracy belief (r = −0.05); Study 2 found that experimentally lowering NFCC via high accountability reduced belief-consistent assimilation of evidence [2]. | Trait closure alone is insufficient; situational closure can sustain prior beliefs [2]. |
| German representative panel (N = 2,883) [4] | NFC had a small positive coefficient (0.08) for COVID-19 conspiracy beliefs, while pre-pandemic political trust (−0.33) and concurrent crisis trust (−0.51) were much stronger; trust did not moderate NFC [4]. | NFC is a minor individual-difference predictor relative to institutional trust [4]. |
| COVID-19 latent profile analysis (N = 319) [5] | Bivariate NFC–conspiracy correlation was weak, but the strongest conspiracy profile had lower NFC (mean 43.96) than the low-conspiracy profile (46.74) [5]. | High-conspiracy believers were not uniformly high in closure; trait-only measurement may miss situational variation [5]. |
| Hungarian fake-news panel (N = 295) [14] | NFC correlated with non-political fake news (r = .26) and anti-government real news (r = .17), and predicted non-political fake news (B = .20), but was not significant for pro-government fake news (B = .002) or anti-government real news in the multivariate model (B = −.153); conspiracy mentality was the consistent predictor [14]. | Closure effects are domain-specific and may disappear once ideology-adjacent variables are modeled [14]. |
| Repetition/illusory truth (seven studies, N = 2,196) [13] | Across trivia statements and partisan news headlines, the illusory truth effect occurred but was not moderated by need for cognitive closure [13]. | Repetition-based acceptance is largely closure-independent [13]. |
| Eyewitness misinformation (three experiments) [8] | NFC augmented retrieval-induced forgetting, which magnified post-event misinformation effects in eyewitness memory [8]. | Closure can affect memory processes that make misleading information more accessible [8]. |

Taken together, these studies do not establish a robust positive main effect of NFC on misinformation acceptance [2][4][5][13][14]. They establish a conditional effect: closure can raise acceptance when a simple false explanation is accessible [1], but it can also reduce conspiracy endorsement when an official explanation is available [1], and it may be small or null when trust, ideology, repetition, or latent-profile differences dominate [4][5][13][14]. The Hungarian fake-news study’s conclusion is that conspiracy mentality, not NFC, consistently explained fake-news belief [14].

## Mechanisms: how closure can increase acceptance

The central mechanism is epistemic urgency: high-NFC people seek a definite answer and then hold it to avoid reopening uncertainty [4]. Conspiracy narratives can satisfy this motive because they provide simple, structured explanations for complex or uncertain events [3][4]. In an online sample (n = 380), avoidance of ambiguity and closed-mindedness related to coronavirus fear through conspiracy beliefs, and need for predictability partially mediated that relation [3]. This can translate into shallow processing and confirmation: high NFC is associated with superficial analysis of incoming information and motivation to seek information consistent with existing knowledge structures, while low NFC is associated with tolerance of ambiguity and careful analysis [3]. High NFCC produces reliance on confirmation heuristics that strengthen existing beliefs, and low NFCC induces systematic processing and greater scrutiny of information [2]. Closed-mindedness may lead people to ignore information that contradicts their beliefs and to rely on preconceptions [3], whereas open-mindedness or epistemic humility predicts lower COVID-19 conspiracy belief [3].

The heuristic-systematic model supplies the general cue-reliance mechanism: under low involvement or low accuracy motivation, recipients rely on noncontent cues such as communicator credibility or perceived audience opinion rather than argument quality, and source-mediated opinion change is less persistent than content-mediated change [11]. This is the theoretical route by which closure might increase acceptance of misinformation when a trusted source, consensus, or familiar framing is salient, although Chaiken’s experiment manipulated involvement rather than NFC [11].

Closure can also operate at the memory level: NFC augmented retrieval-induced forgetting, which in turn magnified post-event misinformation effects in eyewitness memory [8]. Separately, misinformation persistence after correction is associated with failed corrections, non-accuracy motivations, consistency- and self-identity-related motivations, and cognitive fallacies; detailed debunking can sometimes increase persistence, and meta-analytic evidence for science-relevant corrections may be non-significant [9]. The correction literature does not directly test NFC [9], but its effort-reduction framing is conceptually adjacent to closure.

## Boundary conditions and competing predictors

The clearest boundary condition is the availability of an accessible alternative explanation. In Marchlewska et al., the positive NFCC–conspiracy relation reversed when an official non-conspiratorial explanation was provided [1]. In Leman and Cinnirella, high accountability lowered NFCC and nullified the effect of prior conspiracy beliefs on evidence assimilation [2]. Chaiken’s model similarly predicts that when recipients are highly involved and reliability concerns are paramount, they process message content systematically rather than relying on source cues [11].

Institutional trust appears more powerful than NFC. In the German panel, both pre-pandemic political trust and concurrent crisis trust were strongly negatively related to conspiracy beliefs, and NFC did not interact with trust [4]. Leman and Cinnirella also found a negative correlation between close interpersonal trust and real-world conspiracy belief, suggesting that trust deficits may shape conspiracy endorsement independently of closure [2]. In the same German models, education and age were also stronger predictors than NFC, with higher education and older age associated with lower conspiratorial thinking [4].

Cognitive resources matter but are not the same as closure. Higher verbal cognitive ability predicted lower susceptibility to the continued influence effect in a cited prior study [10], and stronger COVID-19 conspiracy beliefs were associated with lower verbal ability in a latent-profile sample [5]. However, the illusory truth effect was robust to cognitive ability and closure across seven studies [13]. Thus, cognitive ability and closure may operate in different misinformation routes: updating versus repetition.

Thinking style and intuition also compete with closure as explanations. Preferences for intuitive versus analytical thinking style increase susceptibility to COVID-19 conspiracy theories [4], and stronger conspiracy believers were more likely to reason emotively in the latent-profile study [5]. A multilevel meta-analysis of 170 studies and 158,473 participants found that the strongest correlates of conspiratorial ideation pertained to perceived danger and threat, reliance on intuition and odd beliefs/experiences, and antagonism/acting superior, with considerable heterogeneity [7]. The supplied abstract does not report a closure-specific pooled estimate [7].

Repetition and fluency form a hard boundary. The illusory truth effect is not moderated by need for cognitive closure [13]. Newman et al., across five experiments, tested need for cognition, not closure, and found little moderation of truthiness; high need for cognition may even increase delayed illusory-truth susceptibility absent a warning [12]. Therefore, a closure-based account cannot explain why repeated false statements feel true [13].

For fake news, deliberation reduces belief in false headlines regardless of political concordance, and the mechanism is framed as lack of reasoning rather than closure [15]. Political orientation also predicts conspiracy beliefs in the German panel, with right-wing orientation associated with higher conspiracy beliefs [4], but the German panel tested trust as a moderator, not political-orientation moderation of NFC [4]. Message features and time pressure remain open: misinformation is more prevalent and persistent on controversial, politically charged topics and often uses emotional, sensational, or threatening features [9], and although time pressure can heighten closure [2], the fake-news load study did not measure NFC [15].

## What the evidence does and does not establish

The conspiracy meta-analysis abstract does not report a closure-specific pooled estimate [7], and the direct tests are heterogeneous across domains [1][4][5][13][14]. The available evidence therefore does not establish a single pooled effect size for NFC across misinformation acceptance.

Several limitations bound these conclusions. The Stefanek study is correlational, used online snowball sampling, and cannot establish causal direction [3]. The Jones latent-profile study found an unexpected negative profile difference and suggests that measuring closure only as a trait may miss situational or cultural variation [5]. The Hungarian fake-news study shows that NFC’s apparent effect depends on the type of headline and the covariates included [14]. The fake-news deliberation study used non-nationally representative MTurk samples and may have missed people most susceptible to misinformation [15]. The executive-function study notes that working-memory updating and intelligence may be difficult to separate and that prior working-memory findings have not consistently replicated [10].

## Conclusion

Need for closure is best understood as a certainty-seeking moderator, not a general cause of misinformation acceptance [4]. It can increase acceptance when a simple false explanation is accessible and when official, accuracy-relevant, or trusted explanations are weak [1][4], but it can also track acceptance of accurate claims [1][14] and has little role in repetition-driven truthiness [13]. The strongest confidence is for the conditional pattern: NFC amplifies accessible explanations [1], trait NFC effects are often small [4], and fluency-based acceptance is closure-independent [13]. Confidence is lower for a stable, domain-general effect because conspiracy, health misinformation, fake-news, and eyewitness studies point in different directions [2][5][8][14]. Interventions that promote deliberation or inoculation may reduce misinformation, but neither directly tests NFC [9][15]. A decisive next step would be a closure-specific meta-analysis and experiments that jointly manipulate accessibility of official explanations, accountability, institutional trust, message repetition, and threat while measuring NFC with validated scales [1][2][4][6][13].

## References

[1] Addicted to answers: Need for cognitive closure and the endorsement of conspiracy beliefs - Marchlewska - 2018 - European Journal of Social Psychology - Wiley Online Library — https://onlinelibrary.wiley.com/doi/10.1002/ejsp.2308
[2] Beliefs in conspiracy theories and the need for cognitive closure - PMC — https://pmc.ncbi.nlm.nih.gov/articles/PMC3694217
[3] The Relationship between the Need for Closure and Coronavirus Fear: The Mediating Effect of Beliefs in Conspiracy Theories about COVID-19 - PMC — https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690611
[4] Frontiers | Need for cognitive closure, political trust, and belief in conspiracy theories during the COVID-19 pandemic — https://www.frontiersin.org/journals/social-psychology/articles/10.3389/frsps.2024.1447313/full
[5] A latent profile analysis of COVID-19 conspiracy beliefs: Associations with thinking styles, mistrust, socio-political control, need for closure and verbal intelligence - PMC — https://pmc.ncbi.nlm.nih.gov/articles/PMC9988712
[6] nfcs short final — https://www.kruglanskiarie.com/_files/ugd/1b977d_efa0f5d5b2094ce18763eb0cfffd345f.pdf
[7] The conspiratorial mind: A meta-analytic review of motivational and personological correlates — https://pubmed.ncbi.nlm.nih.gov/37358543/
[8] The Role of Need for Cognitive Closure in Retrieval-Induced Forgetting and Misinformation Effects in Eyewitness Memory | Social Cognition — https://doi.org/10.1521/soco.2014.32.4.337
[9] Processing of misinformation as motivational and cognitive biases - PMC — https://pmc.ncbi.nlm.nih.gov/articles/PMC11393549
[10] Executive function and the continued influence of misinformation: A latent-variable analysis - PMC — https://pmc.ncbi.nlm.nih.gov/articles/PMC10075451
[11] https://fbaum.unc.edu/teaching/articles/jpsp-1980-Chaiken.pdf — https://fbaum.unc.edu/teaching/articles/jpsp-1980-Chaiken.pdf
[12] Truthiness, the illusory truth effect, and the role of need for cognition — https://pubmed.ncbi.nlm.nih.gov/31935624
[13] Investigating the robustness of the iIlusory truth effect across individual differences in cognitive ability, need for cognitive closure, and cognitive style — https://biblio.ugent.be/publication/8653558
[14] Social Psychological Predictors of Belief in Fake News in the Run-Up to the 2019 Hungarian Elections: The Importance of Conspiracy Mentality Supports the Notion of Ideological Symmetry in Fake News Belief - PMC — https://pmc.ncbi.nlm.nih.gov/articles/PMC8740309/
[15] https://ide.mit.edu/sites/default/files/publications/manuscript_fake_new_fast_slow_01.07.pdf — https://ide.mit.edu/sites/default/files/publications/manuscript_fake_new_fast_slow_01.07.pdf


Please begin the extraction now. Output only the JSON list directly, without any chitchat or explanations.