Need for Cognition (NFC) describes one’s inclination towards and enjoyment of effortful cognitive activities and has been associated with favourable academic outcomes. Yet, recent evidence also points to beneficial outcomes regarding well-being. This review gives an overview of the literature on the role of NFC in well-being in healthy adults by combining random-effects meta-analyses and a qualitative integration of evidence. Studies investigating NFC and facets of well-being were acquired via database searches and a call for unpublished results. Higher NFC was found to be associated with lower neuroticism, anxiety, negative affect, burnout, public self-consciousness, and depression and with higher positive affect, private self-consciousness, and satisfaction (|ρ| ~ .20 with 95% confidence intervals excluding zero for all examined outcomes). While tests for publication and selection bias in the meta-analyses were negative, heterogeneity was often observed. NFC was further associated with aspects of a more stable identity and higher social confidence, while associations with addictive behaviours and physical health were inconsistent. One mechanism driving these patterns seems to be a higher perceived control in individuals with higher NFC that increases active coping, but also reduces the effectiveness of health interventions by fostering a sense of overconfidence in own resources. Thus, this review provides a leverage point for future research on NFC and well-being to improve prevention and intervention.

Since time immemorial, humans have wanted their lives to be pleasant. They want to feel good, not just in a particular moment, but overall, and they are even willing to experience a momentarily unpleasant emotion if it is useful for achieving long-term well-being (Tamir et al., 2017; Tamir & Ford, 2012). However, we have not yet been able to define what factors actually constitute well-being, as the concept is both complex and controversial (Ryan & Deci, 2001). The discord across studies is so vast that a 2016 review by Cooke et al. identified 42 different instruments used to assess well-being. However, there are two main streams of research: Hedonism and eudaimonism. Hedonism refers to well-being as an experience of pleasure regarding all elements of life (Kahneman et al., 1999) and has often been operationalized as Subjective Well-Being (Diener & Lucas, 1999), a combination of life satisfaction, the presence of positive affect, and the absence of negative affect. Eudaimonism construes well-being as the result of fulfilling one’s true nature, meaning that a person is fully engaged in life activities that align with their most deeply held values (Waterman, 1993). Moreover, eudaimonic theories state that hedonism does not lead to well-being per se, because hedonic behaviours can have different short- and long-term effects (Ryan & Deci, 2001). For instance, indulging in foods with lots of added sugars elicits feelings of immediate pleasure and gratification, but increases the risk for metabolic disorders, cardiovascular diseases, and diabetes in the long run (Alam et al., 2022). Therefore, eudaimonic activities are considered essential for well-being, even though they require more effort than hedonic activities (Huta, 2013). Interestingly, when asked to consider how specific eudaimonic and hedonic activities make them feel when engaging in them, participants reported equal levels of competence, happiness, and harmony between the two (Waterman, 1993). So while short-term effects may be perceived to be the same, long-term effects of hedonic and eudaimonic indicators of well-being diverge, and it is these divergences that will bring research closer to understanding well-being (Ryan & Deci, 2001).

So how come people deliberately pursue effortful activities in order to heighten their well-being, when it is well established that effort is something that is actively avoided (Hull, 1943; Inzlicht et al., 2018; Scheffel et al., 2021)? One answer might be found in personality traits such as Need for Cognition (NFC), a stable intrinsic motivation that describes the tendency to engage in and enjoy effortful cognitive activities (Cacioppo et al., 1996). Individuals with high NFC scores are motivated to invest their cognitive resources independent of context, because they enjoy doing so, resulting in process-oriented, active, and alert behaviour (Cacioppo et al., 1996; Fleischhauer et al., 2010). As of now, there is no research regarding the heritability of NFC. Dopaminergic gene variation has been hypothesized to contribute to individual differences in NFC (Strobel et al., 2018), but given the evidence so far, we can only speculate as to what circumstances contribute to the expression of this trait. Cacioppo et al. (1996) suggested that high NFC likely develops as a result of personal values or early experiences, in which the individual learns the superiority of reasoning to physical force or flight when dealing with challenging situations. This makes them more likely to receive positive feedback and, thus, reinforcement, so they develop a sense of mastery which in turn increases their motivation to engage in effortful thinking. In contrast to that stand those with low NFC scores who “tend to act as cognitive misers” (Cacioppo et al., 1996, p. 197). Rather than to engage in effortful thinking, they rely on heuristics and the judgement of others.

Each person’s NFC can be measured on a bipolar continuum using the Need for Cognition Scale (NCS) developed by Cacioppo and Petty (1982). The original scale has 34 items, but its 18-item short form (Cacioppo et al., 1984) is used more frequently, and even a 6-item version has been proposed (de Holanda Coelho et al., 2018). There are multiple translations of the scale, such as the 16-item German form (Bless et al., 1994), a 6-item and an 18-item Spanish form (Falces et al., 2001; Loose et al., 2023) and the 18-item Chinese form (Kao, 1994). Each item is rated on a 5-point Likert scale, either with the labels “agreement”/“disagreement” or “extremely characteristic”/“extremely uncharacteristic”. Items with reverse polarity are inverted, and a sum score is being calculated.

Since the trait definition puts a clear focus on cognitive and not on other types of effort, most research on NFC has concentrated on academic outcomes or problem-solving. Those findings can provide clues regarding the effects that NFC might have beyond performance. A recent meta-analysis showed an association of r = .20 between NFC and academic achievement, moderated by grade level, geographic region, exposure to intervention, and outcome measurement tool (see Q. Liu & Nesbit, 2023). This association likely arises from the fact that those with higher NFC employ deep learning activities rather than memorizing or rehearsing, which contributes to a more profound understanding of the subject matter (Cazan & Indreica, 2014). Findings in high-school graduates support this notion, showing that the positive association between reasoning skills and grade point average was diminished in those with higher NFC scores, which means that NFC compensated for lower reasoning skills (Strobel et al., 2019). This suggests a vital degree of resilience and persistence in those with higher NFC, which leads them to confidently invest their resources in goal pursuit independent of their abilities (Vogt et al., 2022). This might also be why individuals high in NFC have been found to be better at problem-solving (Nair & Ramnarayan, 2000), text-recall (Kardash & Noel, 2000), and decision making (Carnevale et al., 2011), but not at tasks of executive functions, as these are often less complex and thereby do not appeal to the elaborate processing preference of NFC (Gärtner et al., 2021). Conversely, the task performance of individuals with lower NFC scores is worsened and their stress level heightened when they expect the task to be difficult, because they find it more aversive and are less confident in their abilities (Gülgöz, 2001; Heppner et al., 1983; See et al., 2009). In university courses, where tasks are more complex and challenging, students with higher NFC therefore not only perform better, but report higher study satisfaction and lower termination thoughts (Strobel et al., 2017).

These differences between individuals with higher and lower NFC scores suggest that the effects of NFC reach beyond academic accomplishments. Not only because the latter is associated with increased happiness (Otaghi et al., 2019; Tabbodi et al., 2015), but because confident and intrinsically motivated goal-pursuit is beneficial in various areas of life. So what are the findings on NFC those areas of life that are considered important for well-being, such as physical health, social relationships, and psychological state (The WHOQOL Group, 1998)? If eudaimonic activities are effortful yet essential for increasing well-being, then it is likely that those individuals who actively seek out effortful (cognitive) activities have higher well-being than those who rely only on hedonic activities. Dik and Hansen (2008) have even argued that interest as a motivational or affective state predicts well-being, because it “is both pleasant by itself and also leads one to experience a richer, more active life with a broad range of experiences and a broad range of competencies” (p. 95), an assertion that is reminiscent of the concept of NFC itself.

Another definition of well-being that suggests an influence of NFC is the understanding of well-being as a state in which “individuals have the psychological, social, and physical resources they need to meet a particular psychological, social, and/or physical challenge” (Dodge et al., 2012, p. 230). A decrease in well-being occurs when this balance between resources and challenges is tipped in either direction. That a surplus of resources negatively affects well-being might seem counter-intuitive at first, but takes shape in findings such as objective and subjective overqualification being associated with lower job satisfaction (Arvan et al., 2019; Fine & Nevo, 2008; Johnson & Johnson, 2000). Since NFC is an intrinsic motivation to invest cognitive effort, it lowers a person’s apprehension towards challenges (Gülgöz, 2001), increases their problem-solving expectancy (Heppner et al., 1983), and is associated with higher self-efficacy (Kim et al., 2019; Tan et al., 2020). Studies in recent years have suggested that NFC is not only relevant regarding cognitive challenges but also in overcoming challenges in a broader sense (Bye & Pushkar, 2009; Strobel et al., 2017). Consequently, individuals with higher NFC scores likely experience higher well-being, because they are confident that they can rise to the challenge—perhaps even to such an extent that they don’t feel challenged enough, which would lower their well-being. For instance, a person with high NFC scores might be intrinsically motivated to take on more coursework in university and additional extra-curricular activities or hobbies, neglecting rest periods and ending up with increased stress and decreased performance and enjoyment. This would likely be influenced by third variables as well, such as self-efficacy or coping styles, and it is the goal of this review to shed light on these possible mechanisms.

It is vital to understand more about which factors improve or hinder well-being, as is not just a pleasant state in itself, but leads to better physical health (Boehm, 2018) which in turn increases well-being, creating an upward spiral. More and more is known about the variety of stressors that decrease well-being in everyday life, so more and more should be known about the protective factors, especially those with a wide range of impact, such as personality traits. Rather than targeting just one of the many manifestations of well-being, the aim should be to address well-being on the same level of abstraction in order for interventions to have the highest impact. With its ties to eudaimonic well-being and the balance of challenges and resources, NFC seems to meet this level of abstraction. We therefore investigated the association between NFC and well-being in healthy adults in this review with several meta-analyses and a qualitative overview of the literature. Since there has been no overview of this kind before, and research on well-being is mostly done without explicit models (Ryan & Deci, 2001), we approached this association with a very broad search in an effort to include as much of the spectrum of well-being as possible. This search included aspects such as physical health, intervention responsiveness, social behaviours, non-pathological traits and states (e.g. positive and negative affect, neuroticism), and pathological traits and states (e.g. depression, anxiety, addiction). So rather than testing a specific model or mechanism, this review is intended to be a resource for other researchers to develop hypotheses to then test on new data.

2.1. Search Process

An initial literature search was carried out until March 2021. The databases Web of Science, PsycARTICLE, and Google Scholar were searched for the term “need for cognition”. In order to do justice to the multifaceted nature of well-being, we did not include any other search terms. Sources were subjected to a full-text screening if title and abstract indicated that they investigated NFC in healthy adults in the context of a health intervention, physical health, addictive behaviour, social interactions, work life, affect, emotionality, or psychological disorders that are listed in the International Classification of Diseases ICD-10 (World Health Organization, 2016) or the Diagnostic and Statistical Manual of Mental Disorders DSM-V (American Psychiatric Association, 2013). Quantitative studies in English, German, or in another language with easily comprehensible correlation tables were included, as well as studies that were referenced by those we found (snowball system). The final selection included N = 144 sources (Supplementary Figure S1). We later noticed that this selection included four studies investigating high school students. They are listed in the Supplementary References S1 and were removed from the literature review.

After writing a qualitative review it became apparent that there were nine correlates of NFC that appeared frequently enough to be used for meta-analyses: Neuroticism, anxiety, depression, negative affect, positive affect, life satisfaction, private self-consciousness, public self-consciousness, and burnout. To gather even more comprehensive data for these meta-analyses, we repeated the literature search with each of the correlates in conjunction with NFC as search terms, included own unpublished data, and asked other researchers for unpublished data sets or correlations via the e-mail distribution list of the German Psychological Society as well as social media (Strobel, 2022). Again, we only included quantitative studies conducted with healthy adults, in English, German, or with easily comprehensible correlation tables, which used validated instruments to assess the correlate of interest. There were no temporal, geographical, or cultural restrictions. For a comprehensive reference list with all sources that went into the review and the meta-analyses see Supplementary References S2. The composition of each meta-analysis will be detailed in the respective results section. The findings of the studies that were not part of a meta-analysis were grouped and described based on content.

2.2. Transparency and openness

We adhered to the MARS guidelines for meta-analytic reporting (Appelbaum et al., 2018). All meta-analytic data, analysis code, and the search terms and eligible literature per database are available via We used the R software for statistical computing (version 4.1.1; R Core Team, 2021) together with RStudio (version 2021.9.0.351; RStudio Team, 2021) and the R package metafor (version 3.0-2; Viechtbauer, 2010) for meta-analysis. This review project was not pre-registered. When we began the first literature search, we did not expect the project to reach this scope, so we were not able to adhere to the full requirements of the PRISMA guidelines, because we then had prior knowledge about the topic. We made an effort to turn this into an opportunity by conducting an explorative and exhaustive literature search that was not restricted to specific search terms other than the term “need for cognition”, hoping to identify as much of the relevant literature as possible.

2.3. Statistical Analysis

We performed random-effects meta-analysis and employed Fisher Z transformation of correlations to yield pooled effect sizes, but report backtransformed correlations throughout the manuscript. For effect size classification, we refer to the empirical guidelines by Gignac and Szodorai (2016). To assess the amount of heterogeneity, we report the τ2, , and the Q statistic together with its degrees of freedom. While τ2 is an estimate of the variance of the underlying distribution of true effect sizes, and independent of the number and precision of included studies, it is often difficult to interpret (Harrer et al., 2021). Cochran’s Q is the difference between the observed and the estimated effect sizes of the fixed-effect model (Cochran, 1954), and increases with the number and precision of included studies. Derived from Q is Higgin’s & Thompson’s , the percentage of effect size variability that is not caused by sampling error (Higgins & Thompson, 2002). The latter is independent of the number of studies, but not of their precision. Higgins et al. (2003) have proposed to interpret > 25% as low, > 50% as medium, and > 75% as considerable heterogeneity.

Potential publication bias was assessed by the following approaches: 1) Trim-and-Fill (Duval & Tweedie, 2000), 2) Peters’ test (Peters et al., 2006), and 3) PET/PEESE (Stanley, 2017). Each approach provides an adjusted effect size. If the adjusted effect sizes did not deviate from the effect size as determined by random-effects meta-analysis by ± .05, this was taken as absence of publication bias.

Potential selection bias due to different search procedures was assessed as follows: For all outcomes, the effect size based on all identified studies was compared to the effect size based on 1) studies identified via Web of Science only, 2) studies identified via Google Scholar only, 3) published studies only, and 4) reanalysed data only, i.e., data that are not publicly available, but were available for reanalysis because they were own data sets previously published with a different focus or data that were provided by other researchers upon our call for so far unpublished data on the relation of NFC with variables pertaining to our definition of well-being. Again, if the estimates based on the respective reduced data sets did not deviate from the effect size based on all data sets by ± .05, this was taken as absence of selection bias.

The following sections present the results of the review and meta-analyses on NFC and well-being, grouped by content into six sections: Section 1 presents the meta-analyses on neuroticism, anxiety, positive affect, negative affect, and satisfaction, as well as a qualitative perspective on affect, study and job satisfaction, and self-control (evidence from k = 100 sources). Section 2 contains the meta-analyses on depression and burnout, and qualitative results on suicidality (evidence from k = 25 sources). Section 3 presents the last two meta-analyses on private and public self-consciousness, and a qualitative overview over social behaviours, social networks, and sense of self (evidence from k = 38 sources). Section 4 then provides a qualitative perspective on alcohol and drug use, gambling behaviour, and media consumption (evidence from k = 31 sources). Section 5 presents the literature on perceived health, health behaviours and knowledge, and use of medical measures (evidence from k = 24 sources). And lastly, section 6 gives an overview of the effectiveness of cognitively challenging interventions, emotional and motivational interventions, and differences in intervention outcomes (evidence from k = 30 sources). Across all sections, each effect that is not part of a meta-analysis is detailed in the Supplementary Table S1 with information on sample size, population, NFC instrument, construct, and the effect size. Effects from studies that are part of a meta-analysis but also computed interactions, mediations, or moderations, or offered other relevant additional insight into variable relationships in their manuscripts are presented in the qualitative review sections as well.

3.1. Need for Cognition and emotionality and satisfaction

Neuroticism is a personality trait that has been identified as a robust correlate and predictor of many different mental and physical disorders, particularly depression (Enns & Cox, 1997; Lahey, 2009; Ormel et al., 2013). Figure 1 provides a forest plot of the random-effects meta-analysis on the relation of NFC and Neuroticism using all identified studies (k = 41, N = 21.556). NFC and Neuroticism were significantly negatively related, ρ = -.22, 95% CI [-.25, -.19]. We observed medium heterogeneity, τ2 = 0.006, I2 = 73.80%, Q(40) = 197.43, p < .001.

Figure 1.
Forest plot of the relation of Need for Cognition and Neuroticism (k = 41)
Figure 1.
Forest plot of the relation of Need for Cognition and Neuroticism (k = 41)
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Figure 2 shows the results of robustness analyses with regard to publication and selection bias. The effect size estimate remained stable regardless of the method applied to correct for publication bias or of the selection of studies entered into meta-analysis.

Figure 2.
Robustness checks of the relation of Need for Cognition and Neuroticism.

(A) Effect size estimates when applying different methods to assess publication bias, RMA = random-effects meta-analysis, TAF = Trim-and-Fill method, PET = precision-effect test, PEESE = precision-effect estimate with standard errors (see methods section for details); (B) Effect size estimates when applying different selection criteria for study inclusion, WoS = Web of Science

Figure 2.
Robustness checks of the relation of Need for Cognition and Neuroticism.

(A) Effect size estimates when applying different methods to assess publication bias, RMA = random-effects meta-analysis, TAF = Trim-and-Fill method, PET = precision-effect test, PEESE = precision-effect estimate with standard errors (see methods section for details); (B) Effect size estimates when applying different selection criteria for study inclusion, WoS = Web of Science

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Higher levels of neuroticism are characterized by insecurity, anxiety, negative affect, and oversensitivity to stress; aspects to which NFC also showed negative associations: H-NFC individuals had lower anxiety scores and symptoms (see Figure 3), and less anxiety regarding maths, which was the reason for their higher math ability (Maloney & Retanal, 2020). They also reported being more emotionally stable (Yazdani & Siedlecki, 2021) and worrying less about disease recurrence (Kelly et al., 2010), with no significant association to state worry (Meyer et al., 1990).

Figure 3 provides a forest plot of the random-effects meta-analysis on the relation of NFC and Anxiety – comprising measures of state and/or trait anxiety in general or social anxiety in particular – using all identified studies (k = 22, N = 5.588). NFC and Anxiety were significantly negatively related, ρ = -.19, 95% CI [-.25, -.13]. We observed considerable heterogeneity, τ2 = 0.015, I2 = 78.28%, Q(21) = 81.35, p < .001.

Figure 3.
Forest plot of the relation of Need for Cognition and Anxiety (k = 22)
Figure 3.
Forest plot of the relation of Need for Cognition and Anxiety (k = 22)
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Robustness analyses (see Supplementary Figure S2) showed that overall, the effects size of the relation of NFC and Anxiety was somewhat lower when methods to correct for publication bias were applied (mean ρ = -.14). Concerning selection bias, the k = 7 studies found via Web of Science yielded a considerably lower pooled effect size, ρ = -.17, than the k = 7 studies found via Google Scholar, ρ = -.25.

3.1.1. Positive and negative affect

Figure 4 provides a forest plot of the random-effects meta-analysis on the relation of NFC and Positive Affect, mostly measured using the Positive and Negative Affect Schedule (PANAS; Crawford & Henry, 2004). NFC and Positive Affect were significantly positively related, ρ = .20, 95% CI [.14, .25], k = 15, N = 8.012. Again, we observed medium heterogeneity, τ2 = 0.008, I2 = 74.42%, Q(14) = 38.95, p < .001. The effect size estimates remained stable regardless of the method applied to correct for publication bias or of the selection of studies entered into meta-analysis (see Supplementary Figure S3).

Figure 4.
Forest plot of the relation of Need for Cognition and Positive Affect (k = 15)
Figure 4.
Forest plot of the relation of Need for Cognition and Positive Affect (k = 15)
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Figure 5 provides a forest plot of the random-effects meta-analysis on the relation of NFC and Negative Affect, mostly measured using the PANAS. NFC and Negative Affect were significantly negatively related, ρ = -.14, 95% CI [-.20, -.09], k = 11, N = 7.512. Again, we observed medium heterogeneity, τ2 = 0.005, I2 = 67.60%, Q(10) = 32.81, p < .001.

Figure 5.
Forest plot of the relation of Need for Cognition and Negative Affect (k = 11)
Figure 5.
Forest plot of the relation of Need for Cognition and Negative Affect (k = 11)
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When applying methods to correct for publication bias, the effect sizes were somewhat larger, mean ρ = -.20. The selection of studies entered into meta-analysis did not seem to have a sizeable effect (Supplementary Figure S4).

While the meta-analyses of NFC and positive and negative affect pointed to a medium positive and small negative association, respectively, the correlation within studies was often significant for just one of the two constructs. This phenomenon did not appear to be a property of the sample per se, but perhaps a relationship of NFC with items of the PANAS, which are interpreted differently depending on the study context. For instance, NFC was not associated with positive affect but with its subscale measuring interest and activity, as well as with the behavioural activation system (Fleischhauer et al., 2010). Furthermore, H-NFC individuals reported more positive life events and evaluated them particularly positively, which was not the case for negative ones, suggesting a memory bias that benefits well-being (Strobel et al., 2017). On the other hand, H-NFC individuals showed more positive and negative reactions after being asked to write about an emotional experience (Green et al., 2017). The authors argue that the intense cognitive elaboration facilitated by NFC led to intense short-term reactions but likely results in a better long-term integration of experiences. H-NFC individuals showed less experiential avoidance, reacted more mindful to negative thoughts, and were more motivated and confident in applying emotion regulation strategies (Vaughan-Johnston et al., 2020). However, under exceptionally demanding circumstances, the relevance of NFC might decrease, as another study investigated male cancer patients and their partners, and found NFC to be correlated with lower stress, less negative affect, and more positive affect in partners only (Oh et al., 2007). This was attributed to the time of measurement and the partners’ opportunity of bypassing medical information.

3.1.2. Life satisfaction and academia

When pooled over measures of life, study, and job satisfaction, NFC and satisfaction were significantly positively related, ρ = .20, 95% CI [.13, .27], k = 20, N = 9.774, with significant heterogeneity across studies, τ2 = 0.025, I2 = 90.82%, Q(19) = 127.25, p < .001 (Figure 6). When only considering life satisfaction (mostly measured via the Satisfaction with Life Scales; SWLS, Diener et al., 1985), the pooled effect size was very similar, ρ = .18, 95% CI [.08, .27], k = 13, N = 8.002), and heterogeneity persisted, τ2 = 0.029, I2 = 92.90%, Q(12) = 76.91, p < .001, though it is unclear, why. The two studies that reported the lowest (Anthimou et al., 2021) and the highest (Coutinho & Woolery, 2004) effect size both had student samples of the same mean age, who reported the same mean SWLS scores, and—when adjusting for the different response scales—similar mean scores of the 18-item NCS.

Figure 6.
Forest plot of the relation of Need for Cognition and Satisfaction (k = 20).

Single letters next to the N column indicate whether study satisfaction (S), job satisfaction (J) or life satisfaction were assessed in the respective study.

Figure 6.
Forest plot of the relation of Need for Cognition and Satisfaction (k = 20).

Single letters next to the N column indicate whether study satisfaction (S), job satisfaction (J) or life satisfaction were assessed in the respective study.

Close modal

In the robustness analyses with regard to publication and selection bias, the effect sizes were somewhat smaller, mean ρ = -.14, while the selection of studies entered into meta-analysis did not seem to affect effect size estimation (Supplementary Figure S5).

In addition to the medium positive association between NFC and satisfaction, NFC eclipsed religious doubt as a predictor of life satisfaction in religious individuals (Gauthier et al., 2006). NFC also mediated the influence of cognitive performance on life satisfaction, positive affect, and negative affect (Yazdani & Siedlecki, 2021), indicating that those who excel at cognitive tasks are only happier if they also enjoy doing so. This person-environment-fit was reflected in academic contexts, which can also be seen in Figure 6, where four of the six largest effects were found for study or job satisfaction, while most of the effects for life satisfaction were smaller. H-NFC university students not only showed more academic engagement but felt more fostered by their courses (Cole & Korkmaz, 2013) and expected to experience more desirable career events but not more desirable personal events (Klaczynski & Fauth, 1996). H-NFC students were less motivated by the prospect of being outperformed and more motivated by the strive for personal mastery (Tan et al., 2020). This benchmarking of progress based on own past achievements requires accurate self-assessment, which has been linked to positive educational outcomes (Andrade & Valtcheva, 2009), and was also reflected in the lack of association between NFC and anger or pride regarding coursework (Karagiannopoulou et al., 2020). NFC was associated with higher psychological well-being in students (Cole & Korkmaz, 2013), higher study satisfaction, lower termination thoughts (Grass et al., 2017), less dropout (Klaczynski & Fauth, 1996), less college stress (Epstein et al., 1996), less clutter (Prohaska et al., 2018), lower anxiety regarding the coursework (Karagiannopoulou et al., 2020), higher problem solving expectancy (Heppner et al., 1983), higher self-efficacy (Kim et al., 2019; Tan et al., 2020), higher passive and active learning motivation (B. Liu et al., 2020), less naïve optimism, and higher self-esteem (Epstein et al., 1996). However, NFC was associated with better performance but not higher study satisfaction in teacher trainees (Grass et al., 2018). In that study, the majority of the sample was training to be a primary school teacher, who are required to have general rather than specialized knowledge of the course material and to supervise and support the children in their development of basic skills. Individuals who choose to become a primary school teacher might therefore have lower NFC scores altogether, but this was not analysed in the study. Interestingly, procrastination, a common symptom of depression caused by repetitive thoughts (Constantin et al., 2018; Ozer et al., 2014), was actively done by H-NFC students (Zhou, 2019), not on everyday tasks but on decisions where they wanted to consider every possible outcome (Prohaska et al., 2018). Yet, they were not procrastinating out of fear of being wrong (M. M. Thompson & Zanna, 1995) and were able to meet deadlines (Zhou, 2019).

3.1.3. Work life

This procrastination pattern looked different in working adults with high NFC, who showed less procrastination in decision making, despite considering more alternatives (Bouckenooghe et al., 2007), just like students did. Perhaps, the breadth of possibilities that are being considered remains wide throughout the life span, but the time taken to decide shortens as the individual becomes increasingly experienced and knowledgeable. H-NFC individuals were more certain about their roles at work and had higher motivation to work if they had less than four years of experience (Nowlin et al., 2017). Furthermore, H-NFC individuals felt safer at work (Pan et al., 2020), did not engage in interpersonal mistreatment, and their mood was less negatively influenced by colleagues letting off steam, even though they reported more of this behaviour being directed at them (Rosen et al., 2020). However, researchers with high NFC were not only more creative when they felt like creativity was being fostered in their workplace but also when they felt psychologically unsafe (Pan et al., 2020). Higher (malevolent) creativity under threat in H-NFC individuals was also found by Baas et al. (2019), suggesting that H-NFC individuals do not necessarily work better when unsafe but that they purposefully invest resources to improve their situation.

3.1.4. Self-control

This deliberate allocation of resources was a recurring theme in many studies with very consistent findings. It appears that H-NFC individuals not only had higher effortful control (Kührt et al., 2021; Nishiguchi et al., 2016, 2018), i.e. more efficient executive attention, but NFC and effortful control increased each other over time (Nishiguchi et al., 2016). Similarly, H-NFC individuals often reported higher self-control, indicating they are able to regulate their thoughts, emotions, and behaviours more easily (Bertrams & Dickhäuser, 2012; Grass et al., 2018, 2019; Kührt et al., 2021; Sevincer et al., 2017) and with respect to the necessary effort (Tan et al., 2020). Self-control mediated between NFC and self-esteem, and NFC and depressive mood (Bertrams & Dickhäuser, 2012), suggesting a strong dependency between being able to exert self-control and being motivated to do so. Self-control itself has also been negatively linked to various psychopathology measures (Tangney et al., 2004), depressive mood, stress (Finkenauer et al., 2005), and the inability to cope with negative emotions (Gailliot et al., 2006). H-NFC individuals had higher coping abilities (Bye & Pushkar, 2009) and were coping more actively and less passively (Grass et al., 2018). They found advice more helpful for coping in combination with emotional support, stating that the latter was issue relevant and facilitated the processing of the advice (Kim et al., 2019). NFC showed no association to rumination (Nishiguchi et al., 2018; Vannucci & Chiorri, 2018), a judgemental and passive type of self-focus (Trapnell & Campbell, 1999), which has been associated with being overly focussed on the past, pessimistic about the future, and having more negative thoughts (Lavender & Watkins, 2004; Nolen-Hoeksema et al., 2008). Only controlling for effortful control led to a positive association of NFC and rumination (Nishiguchi et al., 2018). Reflection on the other hand was positively associated with NFC (Nishiguchi et al., 2016, 2018) and has been described as a curious and exploring type of self-focus (Trapnell & Campbell, 1999), correlating with reduced depression, more creativity, and enhanced goal formation (Takano & Tanno, 2009; Verhaeghen et al., 2014). Indeed, H-NFC individuals directed their attention more to their own thoughts and feelings about themselves (Berzonsky & Sullivan, 1992), but not in an obsessive way (Ghorbani et al., 2004). They reported being more mindful by being more observing (Noone & Hogan, 2018), and were convinced to be in control of their own thoughts, behaviours, and life events (Bye & Pushkar, 2009; Fletcher et al., 1986; Ghorbani et al., 2004) whereas L-NFC individuals attributed these aspects more to chance or powerful others (Ghorbani et al., 2004).

3.2. Need for Cognition and depression, suicidal tendency, and burnout

Several studies on NFC investigated depressive symptoms, suicidal tendencies, and burnout symptoms, with heterogeneous results across topics and samples.

3.2.1. Depressive symptoms

Figure 7 provides a forest plot of the random-effects meta-analysis on the relation of NFC and Depression, mostly measured via the Beck Depression Inventory-II (BDI-II; Beck et al., 2011) or the Depression subscale of the Depression, Anxiety and Stress Scales (DASS; Henry & Crawford, 2005). NFC and Depression were significantly negatively related, ρ = -.25, 95% CI [-.30, -.19], k = 14, N = 4.109. We observed medium heterogeneity, τ2 = 0.009, I2 = 71.85%, Q(13) = 60.45, p < .001. With regard to publication and selection bias, the effect size of the relation of NFC and Depression was higher when methods to correct for publication bias were applied (mean ρ = -.35), whereas it remained rather stable regardless of the selection of studies (see Supplementary Figure S6).

Figure 7.
Forest plot of the relation of Need for Cognition and Depression (k = 14)
Figure 7.
Forest plot of the relation of Need for Cognition and Depression (k = 14)
Close modal

Two studies additionally investigated the impact of depression on NFC, yielding non-significant (Maschio, 2018) or negative results (Nishiguchi et al., 2016), suggesting that the loss of interest and the repetitive though patterns that are typical for depression might negatively impact the interest- and exploration-driven thought processes of NFC. Assumptions regarding underlying mechanisms varied but self-control emerged in this context just like it did in influencing affect. NFC no longer negatively predicted depression when controlling for effortful control, and the negative impact of depression on effortful control was stronger for L-NFC individuals (Nishiguchi et al., 2016). NFC alone was not sufficient in predicting the course of disease in depressed individuals (Nishiguchi et al., 2016), and higher resource management abilities were only related to lower depressed mood at work for individuals high or average in NFC (V. C. Gallagher, 2012).

3.2.2. Suicidal tendencies

Neither NFC nor NFC and depression could predict suicide risk or behaviours (Cramer et al., 2016, 2019; Cramer, Franks, et al., 2020; Cramer, Langhinrichsen-Rohling, et al., 2020). A proposed interaction was the one of NFC with Need for Affect, the motivation to approach or avoid situations that induce emotions (Maio & Esses, 2001). There was no association of NFC and affect intensity (Epstein et al., 1996), NFC and Need for Affect were either positively (Maio & Esses, 2001) or non-significantly (Aquino et al., 2016) related, and H-NFC individuals reported more affect approach and less affect avoidance motivation (Cramer et al., 2016; Cramer, Franks, et al., 2020). While higher approach motivation decreased suicide risk in a military sample (Cramer, Franks, et al., 2020), it elevated suicide risk in a student sample but only in H-NFC individuals (Cramer et al., 2016). One possible explanation could be that adolescence is characterised by a wide range of new and intense experiences, and those high in NFC who are motivated to navigate all those novel challenges struggle more because they experience them more consciously but do not necessarily have the tools to deal with them yet. Higher avoidance motivation was consistently associated with elevated suicide risk (Cramer et al., 2019; Cramer, Franks, et al., 2020; Cramer, Langhinrichsen-Rohling, et al., 2020) and this effect was heightened by high NFC in young adults who had attempted suicide before (Cramer et al., 2019). In the same sample, increasing levels of NFC lessened the effect of anxiety on suicide risk. When it came to general cognitions about death, H-NFC individuals were more willing to think about death and use that for personal growth (Jennings et al., 2009) rather than resorting to paranormal beliefs (P. Rogers et al., 2018).

3.2.3. Burnout

Across k = 8 studies with a total sample size of N = 5.502, NFC and Burnout (mostly measured via a variant of the Maslach Burnout Inventory; MBI, Maslach et al., 1997) were significantly negatively related, ρ = -.25, 95% CI [-.31, -.18] (Figure 8). There was no significant heterogeneity across studies, τ2 = 0.005, I2 = 65.36%, Q(7) = 12.52, p = .085. Applying methods to correct for publication or selection bias had no sizeable impact on effect sizes (Supplementary Figure S7).

Figure 8.
Forest plot of the relation of Need for Cognition and Burnout (k = 8)
Figure 8.
Forest plot of the relation of Need for Cognition and Burnout (k = 8)
Close modal

The findings regarding NFC and burnout pointed to a medium to large negative association, indicating that H-NFC individuals were less emotionally exhausted, less cynical towards their work, and had higher self-efficacy (Grass et al., 2018; Naderi et al., 2018). Different mechanisms of how NFC impacts burnout scores were observed in different samples: In teacher trainees, more active and less passive coping partially mediated between NFC and burnout (Grass et al., 2018), while in teachers, self-control was a partial mediator when the amount of teaching experience was being taken into account (Zerna et al., 2022), and in students, self-efficacy was found to be a partial mediator (Naderi et al., 2018). These findings suggest that the influence of traits on burnout may be quite context dependent, with coping and self-efficacy being more important in university contexts, which are standardised and less specific, and job experience being more important in work contexts, where coping and knowledge have become job-specific and therefore more effective.

3.3. Need for Cognition and social networks and sense of identity

Social ties and interactions meet some of our most basic human needs and are therefore an essential part of well-being (Greenblatt et al., 1982; Ohrnberger et al., 2017). They also contribute to our sense of identity, a foundation of healthy development (Lecky & Taylor, 1945; C. R. Rogers, 1959) and a prerequisite for well-being (Erikson, 1994).

3.3.1. Social networks and behaviours

NFC showed a medium negative correlation with anxiety in the meta-analysis (Figure 4), which also included studies on social anxiety. Furthermore, NFC was not significantly associated with social desirability (Curşeu & de Jong, 2017), and either not significantly (Meertens & Lion, 2008; Osberg, 1987) or positively (Osberg, 1987) with self-esteem.

There was a medium relation between NFC and Private Self-Consciousness, i.e. the focus on one’s own thoughts and feelings (Fenigstein et al., 1975), ρ = .25, 95% CI [.21, .29], k = 14, N = 2.757 (Figure 9). The test for heterogeneity was insignificant, τ2 = 0.001, I2 = 14.09%, Q(13) = 19.45, p = .110. Publication bias or study selection did not seem to affect effect size estimation (Supplementary Figure S8).

Figure 9.
Forest plot of the relation of Need for Cognition and Private Self-Consciousness (k = 14)
Figure 9.
Forest plot of the relation of Need for Cognition and Private Self-Consciousness (k = 14)
Close modal

Only k = 7 studies with a total sample size of N = 870 could be identified on the relation between NFC and Public Self-Consciousness, i.e. the focus on how others perceive one’s appearance and behaviour (Fenigstein et al., 1975). There was a small significant relation, ρ = -.14, 95% CI [-.21, -.08] (Figure 10). Heterogeneity across studies was insignificant, τ2 = 0.000, I2 = 0.00%, Q(7) = 3.31, p = .769. Publication bias only weakly affected effect size estimation, and there was no effect of selection bias with regard to the relation of NFC and Private Self-Consciousness (Supplementary Figure S9).

Figure 10.
Forest plot of the relation of Need for Cognition and Public Self-Consciousness (k = 7)
Figure 10.
Forest plot of the relation of Need for Cognition and Public Self-Consciousness (k = 7)
Close modal

In the study by Reeves et al. (1995) the private self-consciousness subscale internal state-awareness had a large correlation with NFC, while the other subscale self-reflectiveness had only a small correlation with NFC. Internal state-awareness was associated with lower depression and social anxiety, while higher self-reflectiveness showed the opposite pattern. Public self-consciousness concludes the series of meta-analyses. The results of all meta-analyses are outlined in an overview in Table 1.

Table 1.
Results of the meta-analyses.
Construct Studies Relation Heterogeneity 
k N ρ 95% CI τ2 I2 dfQ Q p 
Neuroticism 41 21.556 -.22 -⁠.25, -⁠.19 0.006 73.80% 40 197.43 < .001 
Anxiety 22 5.588 -.19 -.25, -.13 0.015 78.28% 21 81.35 < .001 
Positive Affect 15 8.012 .20 .14, .25 0.008 74.42% 14 38.95 < .001 
Negative Affect 11 7.512 -.14 -.20, -.09 0.005 67.60% 10 32.81 < .001 
Satisfaction 20 9.774 .20 .13, .27 0.025 90.82% 19 127.25 < .001 
Depression 14 4.109 -.25 -.30, -.19 0.009 71.85% 13 60.45 < .001 
Burnout 5.502 -.25 -.31, -.18 0.005 65.36% 12.52 < .001 
Private Self-Consciousness 14 2.757 .25 .21, .29 0.001 14.09% 13 19.45 .110 
Public Self-Consciousness 870 -.14 -.21, -.08 0.000 0.00% 3.31 .769 
Construct Studies Relation Heterogeneity 
k N ρ 95% CI τ2 I2 dfQ Q p 
Neuroticism 41 21.556 -.22 -⁠.25, -⁠.19 0.006 73.80% 40 197.43 < .001 
Anxiety 22 5.588 -.19 -.25, -.13 0.015 78.28% 21 81.35 < .001 
Positive Affect 15 8.012 .20 .14, .25 0.008 74.42% 14 38.95 < .001 
Negative Affect 11 7.512 -.14 -.20, -.09 0.005 67.60% 10 32.81 < .001 
Satisfaction 20 9.774 .20 .13, .27 0.025 90.82% 19 127.25 < .001 
Depression 14 4.109 -.25 -.30, -.19 0.009 71.85% 13 60.45 < .001 
Burnout 5.502 -.25 -.31, -.18 0.005 65.36% 12.52 < .001 
Private Self-Consciousness 14 2.757 .25 .21, .29 0.001 14.09% 13 19.45 .110 
Public Self-Consciousness 870 -.14 -.21, -.08 0.000 0.00% 3.31 .769 

k = number of studies. N = total sample size. ρ = correlation. CI = confidence interval. τ2 = Tau-squared. I2 = Higgin’s & Thompson’s I2. dfQ = degrees of freedom of Cochran’s Q. Q = Cochran’s Q. p = p-value.

H-NFC individuals were less concerned about communication (Wycoff, 1992) and less appearance-conscious (Reeves et al., 1995) but there were no associations to shyness, sociability, loneliness (Osberg, 1987), or style-consciousness (Reeves et al., 1995). H-NFC individuals reported being less prejudiced and having social networks with a higher demographic variety (Curşeu & de Jong, 2017), which might have also contributed to their higher sense of uniqueness (Pilarska, 2017). Still, they felt no particular attachment to their community or home (Prohaska et al., 2018), used networking sites less often, and were less likely to add friends to their profile (Zhong et al., 2011). Since the impact of networking sites on well-being is very complex (Baker & Algorta, 2016; Frison & Eggermont, 2016), more research is needed to clarify the role of NFC.

H-NFC individuals showed better Theory of Mind performance (Stewart & Kirkham, 2020), reported more certainty regarding cause and effect in social situations (Weary & Edwards, 1994), less vulnerable narcissism, i.e. negative emotions, entitlement, and egocentricity (Littrell et al., 2020), higher tolerance for disagreement, less verbal aggressiveness (Linvill et al., 2016), and less anger when others do not apologize (R. L. Thomas & Millar, 2008). Patients with a borderline diagnosis, a mental disorder characterized by severe interpersonal dysfunction, had lower empathy but not different NFC scores than healthy controls, and lower empathy but not NFC strengthened their tendency to attribute others’ behaviours to traits (Homan et al., 2017). However, other studies did not find associations of NFC to state or trait anger (Olson et al., 1984), grandiose narcissism, i.e. dominance, aggression, and immodesty (Littrell et al., 2020), or to the awareness and use of affective cues to guide communication (Booth-Butterfield & Booth-Butterfield, 1990). This indicates that cognitive and affective processing styles can indeed be distinct from one another when it comes to specific constructs. So while in previously mentioned studies NFC was associated with Need for Affect, this association was likely driven by their conceptualization as traits that lead to active seeking behaviour, not because NFC and affective styles are related per se. H-NFC individuals were also less susceptible to social cues when reading news articles online (Dvir-Gvirsman, 2019), but they showed greater confirmation bias (Knobloch-Westerwick et al., 2020). However, the latter study presented liberal and conservative American news articles for the participants to browse freely, so H-NFC participants might have categorized the articles based on headlines and then chosen to read the ones that aligned with their political positions in order to avoid negative emotions, while L-NFC participants might have browsed randomly. This utilization of contextual cues might also explain why H-NFC participants developed more malevolent ideas under threat but not more neutral or benevolent ideas (Baas et al., 2019), as the study presented them with prisoner’s dilemmas, perhaps thereby incentivizing them to invest cognitive effort into immersing themselves in that situation. The enjoyment of cognitive effort was also present in the association of NFC with a clear preference for competent social circles but not for emotional warmth (Aquino et al., 2016). When faced with a choice between varyingly competent and warm social groups, H-NFC individuals preferred the highly competent but emotionally colder ones and identified with them the most (Wolf et al., 2017). Additionally, teams with higher NFC performed better on a task but did not perceive their cooperation to be better (Schei et al., 2020).

3.3.2. Sense of identity

NFC was not associated with the search for or the presence of meaning in life (Carney & Robertson, 2018), but H-NFC individuals emphasized values, goals, and hopes in their identity more than social aspects (Berzonsky & Sullivan, 1992), which aligns with their conviction to be in control over one’s thoughts, emotions, and life events, and they reported a stronger sense of identity through various coping mechanisms (Pilarska, 2015, 2017). They were able to reflect more thoroughly on events, thoughts, and emotions, and integrate them into their sense of self (Littrell et al., 2020; Pilarska, 2015) with a greater sense of continuity, coherence, and contents (Pilarska, 2017). H-NFC individuals adapted events less to fit their sense of self and vice versa, resulting in a more defined sense of boundaries, higher perceived self-worth (Pilarska, 2017), and higher stages of identity development over time (Njus & Johnson, 2008). Sense of identity can be threatened or even lost in schizophrenic patients (Buck et al., 2013) but NFC was negatively associated with the schizotypy subfactors, indicating that H-NFC individuals were less likely to experience cognitive disorganization, emotional flatness, asocial behaviour, and unstable mood in social situations (Broyd et al., 2019; Denovan et al., 2020).

Gender differences were identified in two studies. H-NFC men had fewer sexual partners and a less secure relationship to their father, while this was not true for women (Epstein et al., 1996). H-NFC women reported lower conflict resolution and a more dismissive relationship prototype, while men did not (Epstein et al., 1996). Additionally, the influence of different coping mechanisms on sense of identity varied in men and women (Pilarska, 2017) but these relationship styles and gender differences were not investigated in any other study so far, so more research on these associations is needed.

Overall, the thorough cognitive processing associated with NFC appeared to enable the development of a strong sense of identity and the self, as well as the ability to deal with inconsistencies and contradictions. This in turn facilitated confident handling of social situations but went along with a preference for social networks that were socially diverse, and highly competent but less emotionally warm, just like H-NFC individuals perceived themselves.

3.4. Need for Cognition and substance abuse and addiction

Findings regarding NFC and various addiction behaviours such as drinking, smoking, gambling, and technology use were quite mixed, pointing to interaction effects once more.

3.4.1. Substance abuse and gambling

In students, NFC was not associated with disinhibition (Olson et al., 1984). Students with higher NFC reported having fewer alcohol-related problems and less heavy drinking in some studies (Bernstein et al., 2016; Blanchard et al., 2016) but not in others (Capone & Wood, 2009). Gender effects were also inconsistent, showing less heavy drinking (Hittner, 2004) and higher levels of distrust in women (Epstein et al., 1996), while in men NFC was either associated with less heavy drinking (Epstein et al., 1996) or showed no association (Blanchard et al., 2016; Hittner, 2004). In smokers, NFC was not related to the number of daily cigarettes or past quit attempts but to higher confidence in being able to quit (Haug et al., 2010). Only H-NFC smokers with high perceived vulnerability were less prone to believe in false cigarette health claims (Shadel et al., 2006). These mixed findings regarding substance consumption indicate that the influence of NFC might be eclipsed by other predictors. Higher alcohol-consumption in young adults has been associated with being male, consuming coffee and cigarettes, being single, having alcohol-consuming peers, and having parents with high socio-economic status, while factors such as years of education showed no association (La Fauci et al., 2019; Nazir & Thabassum, 2022). Since NFC is not associated with gender (Trogrlic & Vasic, 2009), but with higher parental education (Popoviciu et al., 2011), and conceptually with more years of education, it does not clearly align with a profile of solely risk or protective factors.

H-NFC individuals were more likely to engage in strategic than non-strategic gambling (Mouneyrac et al., 2018) and even though they did not make more complex decisions (Zadelaar et al., 2020), their performance in a gambling task was either as good as or better than the performance of L-NFC individuals (Harman, 2011). Associations of NFC with impulsiveness or risk taking behaviour were either non-significant (Meertens & Lion, 2008; Xu & Cheng, 2021) or negative (Littrell et al., 2020; Meertens & Lion, 2008), but associations with sensation seeking (Fleischhauer et al., 2010; Shi et al., 2010) and with a preference for immediate satisfaction of needs were positive (Shim et al., 2018). However, H-NFC individuals showed higher inhibitory (Nishiguchi et al., 2016) and self-control, even after adjusting for social desirability (Bertrams & Dickhäuser, 2012).

3.4.2. Media consumption

NFC and boredom proneness were either non-significantly (Olson et al., 1984) or negatively associated (Watt & Blanchard, 1994), and being bored actually increased H-NFC individuals’ creativity (Park et al., 2019), supporting the notion that they not only enjoy but actively seek out cognitive effort. They were less likely to watch television to pass time, reported lower motivations for viewing, watched less (Henning & Vorderer, 2001), and were less likely to aimlessly switch channels (Shim et al., 2018). NFC was not associated with attitudes towards binge watching but H-NFC individuals engaged in this behaviour more (Shim et al., 2018), especially if they were fans of a series (Shim & Kim, 2017). Additionally, NFC was associated with equal or higher identification with an interactive rather than traditional game narrative (Green & Jenkins, 2020).

The patterns of internet and technology use also suggest that NFC is associated with a preference for novel stimuli and challenges, rather than engaging in monotonous or repetitive behaviours. H-NFC individuals were not more likely to busy themselves with multiple electronic devices at once (Zhong et al., 2011), used their smartphone less (Shim et al., 2018) and with higher perceived efficacy (Darvishi et al., 2020), which was also true for their internet use, which showed healthy usage patterns (Shi et al., 2010). Male consumers of internet pornography with higher NFC were less likely to be addicted to it, lose control of consumption, have social problems because of it, and spent less time consuming than those with lower NFC (Antons et al., 2019). Regarding the consumed content, H-NFC individuals showed equally negative attitudes towards different abuse scenarios, while attitudes of L-NFC individuals varied depending on the sexes in the scenario (Leone et al., 2019).

H-NFC individuals reported less impulse buying (Lins & Aquino, 2020) and were less susceptible to nudging (Ingendahl et al., 2020), but this was also the case in situations with beneficial nudges, e.g. ones leading to healthier products (Grandi et al., 2020).

To sum up, the associations of NFC and addiction differed a lot from behaviour to behaviour. Further investigations need to clarify the relationship of NFC and substance consumption, including the role of gender differences and perceived vulnerability. Internet usage patterns were less problematic in H-NFC individuals. They were drawn to activities that met their need for cognitive challenge, such as strategic gambling and binge watching.

3.5. Need for Cognition and physical health

In terms of physical health, the fact that H-NFC people are more likely to engage in cognitive activity appears to benefit their overall health, as they are more knowledgeable and confident about healthy behaviours. H-NFC individuals rated their health slightly higher than (Epstein et al., 1996; Yazdani & Siedlecki, 2021) or equal to L-NFC individuals (Bye & Pushkar, 2009). They had more knowledge regarding diseases and healthy behaviours (De Pelsmacker et al., 2017; Holch & Marwood, 2020; Laws et al., 2020; Osberg et al., 2008; Riley et al., 2019; Williams-Piehota et al., 2006) and felt more confident in evaluating such information (Maki & Feeley, 2021; Vainio, 2019). H-NFC individuals consumed more fruits and vegetables (Williams-Piehota et al., 2006) and plant-based meat alternatives out of environmental and health motives (Vainio, 2019). However, they were less likely to try new foods due to lower materialism scores (Tuncdogan & Ar, 2018) and no association was found to red meat consumption (Vainio, 2019). Even though NFC was not associated with the motivation to use a fitness tracker (Attig et al., 2019) and H-NFC individuals were less active during the week, they were equally active on the weekend (McElroy et al., 2016) or even more active than L-NFC individuals (Yazdani & Siedlecki, 2021). NFC in general was associated with higher intentions to use sun protection (Occa et al., 2020) but with lower skin appearance concern in sunbathing students (McMath & Prentice-Dunn, 2005). The latter study investigated light-skinned students who had intentionally tanned before, deliberately excluding those who do not expose themselves to sunlight for health or appearance reasons, so these findings are not representative. An increase in self-rated health could predict an increase in NFC across four years, while sleep deprivation and binge drinking had the opposite effect, and smoking had no influence (Chen & Chen, 2019). Sleep deprivation did not impact cognitive performance in H-NFC individuals (Kobbeltvedt et al., 2005). However, since Chen and Chen (2019) did demonstrate a link between NFC and long-term sleep deprivation, the findings of Kobbeltvedt et al. (2005) might be due to the fact that they heavily manipulated sleep deprivation over multiple days, so the H-NFC cadets might have been aware of their overall research question and intentionally tried to prove that they invest cognitive effort nonetheless.

Regarding specific diseases, associations with NFC were mixed. Healthy H-NFC individuals only had more correct assumptions about the causation of diabetes but not of colorectal cancer (Riley et al., 2019) and not more knowledge regarding the risk factors of either disease (Hay et al., 2020). Additionally, NFC in healthy individuals was also not associated with hypochondriasis (Bagby et al., 1986) or attitude towards vaccination (Tomljenovic et al., 2020), suggesting that other factors such as personal experiences and norms of the social milieu might be more important here. NFC was also not associated with objective HIV risk or intention to get HIV tested (Maki & Feeley, 2021), as HIV risk is mostly influenced by the partner’s HIV status (Priya et al., 2023) and sexual behaviours (Singh & Saini, 2007). However, H-NFC individuals who were affected by a certain disease knew more about it and adhered more rigorously to their treatment (Hadj-Abo et al., 2020; Laws et al., 2020). Healthy H-NFC individuals were also more likely to discuss prescription medication with their doctor (Krezmien et al., 2011) but this was not true for H-NFC women, who knew more about breast cancer but were still less likely to seek information, consultations, or a screening because they had lower anxiety (De Pelsmacker et al., 2017).

Overall, NFC appeared to facilitate healthy day-to-day behaviours through more health knowledge and literacy but this effect was less pronounced regarding diseases and medical measures, maybe due to a sense of overconfidence in H-NFC individuals, reflected in higher health risk taking behaviour (Zadelaar et al., 2020).

3.6. Need for Cognition and the effectiveness of health interventions

The assumption underlying NFC and health interventions is that H-NFC individuals are more receptive for cognitively stimulating materials because of their preference for cognitive challenge. Several studies found evidence for this assumption but many other studies did not.

3.6.1. Cognitively challenging interventions

Higher NFC was associated with higher risk perceptions after factual rather than emotional message frames in occasional smokers (Stevens et al., 2019; Vidrine et al., 2007) but not in daily smokers (Vidrine et al., 2007), since interventions targeting high-risk groups are generally less effective than others (Carey et al., 2007). In another study, a message emphasizing cognitive benefits did not increase physical exercise behaviour, regardless of NFC, but a message emphasizing affective benefits did increase it for L-NFC individuals (Conner et al., 2011). Similarly, L-NFC individuals felt more persuaded by a testimonial message than a factual one, while H-NFC individuals felt equally persuaded by both because perceived transportation was not tied to persuasion for them (Braverman, 2008). However, NFC and general health-promoting message frames did not interact to predict risk knowledge retention (Stevens et al., 2019), behavioural intentions (Maki & Feeley, 2021; Stevens et al., 2019), or actual behaviour (Latimer et al., 2007; Williams-Piehota et al., 2006). After a detailed message, the intentions of H-NFC individuals were actually lower than those of L-NFC individuals, while a non-detailed message did not differ between groups (Latimer et al., 2007). These findings suggest that while interventions with an affective emphasis are more effective for L-NFC individuals, interventions with a cognitive emphasis can even decrease intention or behaviour in H-NFC individuals to some extent, perhaps because the acquired knowledge heightens their sense of self-efficacy to regulate the behaviour in question.

3.6.2. Other intervention types

H-NFC individuals were more responsive to loss than to gain framed messages (K. M. Gallagher & Updegraff, 2011; Lin et al., 2017; Stevens et al., 2019) and were more sensitive to opportunity costs (Yan & Otto, 2020) but these frames neither impacted content recollection nor behavioural intention (Stevens et al., 2019). Personalized messages had higher long-term impact on self-efficacy for H-NFC individuals compared to no message (Haug et al., 2010) but person-centeredness did not interact with NFC regarding helpfulness or behavioural intention (Gallivan, 2020; Rack et al., 2008). Still, a motivational one-on-one intervention had higher impact on behavioural outcomes for H-NFC than for L-NFC individuals (Capone & Wood, 2009), again emphasizing the importance of self-efficacy in conjunction with NFC. Similarly, verbal metaphors were perceived as more effective by H-NFC individuals than visual metaphors but they did not differ in their impact on behavioural intentions (Occa et al., 2020). In response to high-threat messages, H-NFC individuals were less hopeless (McMath & Prentice-Dunn, 2005), had higher behavioural intentions, and more attitude change (Ruiter et al., 2004), while L-NFC individuals reported the opposite. However, high-threat messages did not differ in impact on actual behaviour depending on NFC (Ruiter et al., 2004). Perhaps, the threat to one’s sense of self-efficacy was more salient for H-NFC individuals because they did report higher self-efficacy than L-NFC individuals did (Holch & Marwood, 2020). And since self-efficacy mediates between behavioural intentions and actual behaviour longitudinally (Hohmann & Garza, 2022) and the study by Ruiter et al. (2004) was cross-sectional, one might argue that the intentions take time to manifest in behavioural change. Generally, H-NFC individuals reported higher individual and situational interest in the presented materials (C. L. Thomas & Kirby, 2020) and their beliefs after an intervention were more stable over time and more resistant to counter-persuasion (Haugtvedt & Petty, 1992). Additionally, attitudes and behavioural intentions were more strongly linked in H-NFC individuals (Horcajo et al., 2019).

3.6.3. Intervention outcomes

Following an intervention, individuals high in NFC showed higher knowledge retention (Haugtvedt & Petty, 1992; Stevens et al., 2019), lower frequency of the harmful behaviour (Haug et al., 2010), higher intervention adherence (Kelders et al., 2013), higher intention to change the harmful behaviour within the next few days (Gallivan, 2020), higher ratings of positive and lower ratings of negative emotions, a pattern that increased over the course of the intervention (Czuchry & Dansereau, 2004), and development of more correct beliefs (Kessler et al., 2019). On the other hand, no associations were observed regarding the development of incorrect beliefs (Kessler et al., 2019), the intention to change the harmful behaviour within the next month (Gallivan, 2020), risk perception (Stevens et al., 2019), behavioural intentions (McMath & Prentice-Dunn, 2005; Stevens et al., 2019), efficacy beliefs (Ruiter et al., 2004), perceived message effectiveness (Occa et al., 2020), and with the frequency of the desired behaviour at follow-up (Williams-Piehota et al., 2006). These findings are surprising, given that they do not fit into the previously theorized pattern of higher self-efficacy and behavioural intentions in H-NFC individuals. Moreover, NFC was even associated with lower perceived message helpfulness (Latimer et al., 2007), higher frequency of the harmful behaviour at follow-up (Bernstein et al., 2016), and higher intention regarding the harmful behaviour after the intervention (Gallivan, 2020). Perhaps some interventions increase the sense of self-efficacy in H-NFC individuals to such an extent that the intended effect reverses, and an increased perception of control lowers intentions and behaviour change. This would be supported by findings regarding the first months of the Covid-19 pandemic in 2020, which was a period of high anxiety, anger, and low perceived control for many people (Tinlin et al., 2021). During this time, H-NFC individuals reported higher compliance with mask-wearing and social distancing, more positive attitudes towards mask-wearing (Xu & Cheng, 2021), higher optimism, and no association to panic buying behaviour or to the extent of feeling affected by the pandemic (Lins & Aquino, 2020).

Regarding general characteristics, NFC was associated with factors that are likely to benefit adherence and success, such as self-efficacy (Holch & Marwood, 2020), self-control (Xu & Cheng, 2021), persistence and self-discipline, higher intrinsic and lower extrinsic motivation (Amabile et al., 1994), and showed no association with reward dependence (Fleischhauer et al., 2010). Only one study found a negative association to mastery beliefs (Double & Birney, 2016), the conviction to be in control over one’s life. This study investigated older adults, and it has been shown that in this age group, past circumstances and recent stressors are the most important factors influencing mastery (Pearlin et al., 2007), and the H-NFC participants might have evaluated these more consciously or elaborately, which would have lowered their sense of mastery.

Ultimately, H-NFC could neither guarantee intervention effectiveness nor intervention adherence, but designing interventions with respect to the different preferences will contribute to intervention impact for both L-NFC and H-NFC individuals.

The aim of this review was to provide an overview of the role of NFC in well-being. Online databases were browsed manually to identify eligible literature, purposefully keeping the concept of well-being broad in order to do justice to its multifaceted nature. Constructs that appeared frequently were subjected to a second, targeted search to collect studies for meta-analyses on neuroticism, anxiety, positive and negative affect, satisfaction, depression, burnout, and private and public self-consciousness. These findings were also reviewed qualitatively along with findings on self-control, suicidality, social behaviours, sense of identity, substance use, media consumption, physical health, health knowledge and behaviours, and the effectiveness of different intervention types. The type of influence NFC had, as well as the unanimity of studies, varied between these sections. The following paragraph provides a summary of the core findings.

4.1. Summary of main findings

H-NFC individuals score lower in neuroticism and report higher positive and lower negative affect. Consequently, they report higher satisfaction, likely resulting from thoroughly processing not only the events in their life but also their own reaction to them. This is supported by the associations of NFC with higher self-control, which stand in a reciprocal relationship with NFC, enhancing one another over time. Therefore, H-NFC individuals do not exert negative self-focus but reflect on their own thoughts in a curiosity driven, observing way. This aligns with previous research showing that H-NFC individuals engage in more meta-cognition, meaning they only use their thoughts to form judgements if they evaluate them as being valid (Briñol & Petty, 2022). They are happier and perform better in environments that foster this type of cognition, not only in academic settings but also in their social networks. The latter are preferred by H-NFC individuals to be more diverse and competent rather than emotionally warm, as they perceive to share these characteristics. NFC is not only related to being more confident and considerate in social interactions but also to being able to integrate experiences and thoughts effectively into a stable, coherent, and sophisticated sense of identity. Overall, H-NFC individuals have lower depression scores, which are often facilitated by a protective effect of effortful control, but the relationship of NFC and suicidal tendencies is more complex due to influential third variables like Need for Affect and sample characteristics. Equally dependent on sample characteristics are the mediators of lower burnout scores in H-NFC individuals, ranging from work experience to coping styles to self-efficacy. Their higher self-efficacy also makes them more confident in being able to quit smoking, even though the associations with consumption of nicotine and alcohol are often non-significant or possibly dependent on third variables like gender. Other addictive behaviours such as gambling and entertainment consumption are also not negatively associated with NFC per se, but H-NFC individuals show these behaviours in ways that meet their need for cognitive challenge, e.g. by choosing strategic games or by binge watching. However, patterns of internet and media usage are healthy in H-NFC individuals, and they are not prone to developing a shopping addiction. Regarding diet and exercise, H-NFC individuals display favourable behaviour as well, and they feel more confident in evaluating health-related information. In patients with a chronic disease, NFC is associated with better disease self-management but in healthy individuals NFC is largely unrelated to knowledge or attitudes regarding medical treatments or preventative measures. Interventions with different message frames are often able to increase such knowledge in H-NFC individuals but these interventions have little effect on attitudes or behavioural intentions and sometimes even end up changing intentions for the worse. Conversely, L-NFC individuals benefit more universally from health interventions, even though they have lower scores on characteristics that are beneficial for intervention success. Ultimately, H-NFC individuals might fall into a false sense of security, perceiving to be in control of their behaviour to such an extent that would allow them to change it anytime (see section 4.3. for a more in-depth discussion of this).

4.2. Interaction of NFC and self-control

H-NFC individuals’ perception of being in control – and being able to exert control – is a recurring theme and might even explain the results of papers that did not make it a subject of discussion. The higher preference for control in H-NFC individuals was first proposed by Cacioppo et al. (1996), who claimed that higher levels of NFC might develop as a result of a high need for structure or control in those who have the skill, ability, and inclination to do so. The origin of this proposal was the highly significant correlation of NFC and desire for control, identified by Thompson et al. (1993). Bye and Pushkar (2009) further elaborated on this, suggesting that what sets desire for control apart from NFC is the aspect of joy: Only those individuals with a high desire for control, who perceive the engagement in effortful cognitive activities as joyful, pave the way for the development of NFC. Various areas showed a conclusive picture of an improvement in well-being through higher NFC and a higher sense of control, suggesting a balance of resources and challenges as established in the definition of well-being by Dodge et al. (2012). H-NFC individuals deliberately and carefully process life events and thoughts, yielding a more stable and sophisticated sense of identity, with more concern about aspects of their identity they were actually able to influence and less concern regarding aspects like appearance. Instead of being stuck in spirals of negative thought, H-NFC individuals direct their attention to positive events and are optimistic about such events happening in the future, especially when they involve cognitive challenge. H-NFC individuals extend their deliberate and careful processing to challenging situations, coping actively, which is reflected in lower burnout scores and better disease management in the chronically ill. As a result, they are less anxious because they feel like they were able to master the situation.

4.3. NFC and the risk of resource overestimation

However, this low level of anxiety also increases their sense of security in situations where low anxiety levels are driving unhealthy behaviours, such as substance use and medical measures. This poses the question whether H-NFC individuals’ higher reported self-control mirrors actual abilities or indicates a degree of overconfidence. The latter is highly probable, since a recent study found no association between NFC and performance in various tasks of executive functioning (Gärtner et al., 2021). Other than in educational contexts where NFC is often associated with higher achievements, likely due to more in-depth learning techniques, performance on executive functioning tasks are not influenced by preparation because there usually is none. As such, these tasks would demonstrate that there is no difference in actual ability depending on NFC. This stands in stark contrast to the fact that NFC showed correlations above r = .50 with non-ability-based confidence in one’s processing speed, fluid intelligence and crystallized knowledge, higher correlations than any other trait assessed in that study had (Vogt et al., 2022). This could also be an alternative interpretation of the finding that NFC mediates the influence of cognitive performance on life satisfaction and positive and negative affect (Yazdani & Siedlecki, 2021)—higher NFC might increase well-being because it increases the confidence in one’s own abilities. However, this could be a potential pitfall for H-NFC individuals in situations where they report high abilities in the form of perceived control and self-efficacy but show no differences in behaviour, like smoking cessation, preventative health screenings, and health interventions with different message frames. Perceiving to be able to quit smoking anytime but not doing so (Haug et al., 2010), to know enough about a health condition not to consult a physician (De Pelsmacker et al., 2017), and to use intervention messages as a method of knowledge gain rather than to be persuaded by them, can lead to overconfidence and a false sense of security. Regardless of whether H-NFC individuals are actually able to use the abilities they perceive to have, the behaviours resulting from their sense of security are not favourable, taking shape in health interventions having the opposite effect, lack of interest in medical appointments, preference for strategic gambling (Mouneyrac et al., 2018), and so on. While L-NFC individuals were demotivated after a high-threat intervention (McMath & Prentice-Dunn, 2005), perhaps because their low confidence in their abilities decreased even further, H-NFC individuals were not, but they also did not change their behaviour (Ruiter et al., 2004). And after a detailed intervention, which would have provided them with more resources in the form of information, their behavioural intentions even decreased (Latimer et al., 2007). It seems that if NFC is paired with an explicit feeling of having insufficient resources or abilities, interventions are more likely to succeed, as only H-NFC smokers with high perceived vulnerability did not fall for false cigarette claims (Shadel et al., 2006). The possibility for ineffective or even backfiring interventions has also been proposed by Liu and Nesbit (2023) who wrote that “Need for Cognition may interact in varied and possibly unpredictable ways with instructional interventions” (p. 21). Returning to the definition of well-being by Dodge et al. (2012), this overconfidence in H-NFC individuals can be interpreted as an imbalance of resources and challenges, which is caused by (the perception of) an excess of resources and results in a decrease in well-being. Even if this decrease in well-being is not immediately perceived as such, it will most likely manifest over time in the form of an increase in health risks, which arise from a lack of preventative measures, screenings, and unchanged noxious behaviours. It is a promising approach for future studies to investigate the effects of NFC in the light of this perception of resources. Initial evidence from our own research shows that H-NFC teachers have lower burnout scores because they perceive external demands as more fitting to their own resources and less as exceeding them (Zerna et al., 2022). And exploring data from a Registered Report on effort discounting (Zerna et al., 2023) indicated that H-NFC participants found the difficult levels of a working memory task less aversive and valued them more, even though their performance did not differ from that of L-NFC participants. Ultimately, most of the negative impact is being outweighed by direct and indirect positive associations of NFC with a heightened sense of well-being, but health professionals should be aware of the possibility of an overconfident sense of control in H-NFC individuals.

4.4. Limitations

The exploration of the role of NFC in well-being is by no means exhausted. There are still many open questions regarding underlying mechanisms in areas where the results are particularly ambiguous, like alcohol consumption. As there are indications of reciprocal effects of NFC with other variables, more longitudinal research would shed light on how these mechanisms influence other outcomes. Furthermore, most samples are university samples, where NFC can be expected to be generally higher and narrower in range, and findings regarding suicidal tendencies show a clear dependence of results on the sample. Clinical samples are underrepresented as well, as there are hardly any investigations into NFC and mental disorders beyond depression. Healthy adults are the focus of this review, so we cannot say whether the findings and mechanisms identified here also extend to adolescents and children.

Furthermore, we observed heterogeneity in all meta-analyses. The cause of this heterogeneity can be investigated with meta-regressions to identify moderating variables, such as gender, age, sample characteristics, and the instrument used to assess NFC and its correlate. However, as this research area is quite young, there is not a lot of theoretical work to support the selection of adequate moderators. An inadequate selection would in turn lead to a Type-I-error inflation. Furthermore, not all of the meta-analyses contain enough studies for a meta-regression (more than ten is recommended by the Cochrane handbook (Higgins et al., 2019)), and it is likely that not all of the studies report every variable to the same precision. For these reasons, and given that the effect sizes are surprisingly consistent across the meta-analyses, we refrained from conducting meta-regressions. We encourage future research to investigate possible moderating and confounding variables.

4.5. Conclusion

Despite the extensive literature screening and the call for unpublished results, it is still possible that not all relevant studies were found. Moreover, the diversity of studies necessitated a split into several meta-analyses on one hand and a qualitative review on the other hand. However, this provided a quantitative framework while allowing a broad inclusion of topics and research designs. As a result, this broad overview, including research gaps, ambiguities, and underlying themes, provides a good starting point to further investigate NFC as a factor that can both reinforce and jeopardize personal well-being.

Contributed to conception and design: JZ, AlS, AnS

Contributed to acquisition of data: JZ, AlS

Contributed to analysis and interpretation of data: JZ, AlS

Drafted and/or revised the article: JZ, AlS, AnS

Approved the submitted version for publication: JZ, AlS, AnS

The authors declare no competing interests.

The Supplementary Material file can be accessed via

The analysis code for the meta-analyses, the bib-files of hits per database, the xlsx-files with data for each meta-analysis, the figures, and the search terms and number of hits per database can be accessed via

Alam, Y. H., Kim, R., & Jang, C. (2022). Metabolism and Health Impacts of Dietary Sugars. Journal of Lipid and Atherosclerosis, 11(1), 20–38.
Amabile, T. M., Hill, K. G., Hennessey, B. A., & Tighe, E. M. (1994). The Work Preference Inventory: Assessing intrinsic and extrinsic motivational orientations. Journal of Personality and Social Psychology, 66(5), 950–967.
American Psychiatric Association (Ed.). (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). American Psychiatric Publishing.
Andrade, H., & Valtcheva, A. (2009). Promoting Learning and Achievement Through Self-Assessment. Theory Into Practice, 48(1), 12–19.
Anthimou, A., Koutsogiorgi, C., & Michaelides, M. P. (2021). Psychometric properties of the Satisfaction with Life Scale in a Cypriot student sample. Psychology: The Journal of the Hellenic Psychological Society, 26(3), 273–282.
Antons, S., Mueller, S. M., Wegmann, E., Trotzke, P., Schulte, M. M., & Brand, M. (2019). Facets of impulsivity and related aspects differentiate among recreational and unregulated use of Internet pornography. Journal of Behavioral Addictions, 8(2), 223–233.
Appelbaum, M., Cooper, H., Kline, R. B., Mayo-Wilson, E., Nezu, A. M., & Rao, S. M. (2018). Journal article reporting standards for quantitative research in psychology: The APA Publications and Communications Board task force report. American Psychologist, 73(1), 3–25.
Aquino, A., Haddock, G., Maio, G. R., Wolf, L. J., & Alparone, F. R. (2016). The role of affective and cognitive individual differences in social perception. Personality and Social Psychology Bulletin, 42(6), 798–810.
Arvan, M. L., Pindek, S., Andel, S. A., & Spector, P. E. (2019). Too good for your job? Disentangling the relationships between objective overqualification, perceived overqualification, and job dissatisfaction. Journal of Vocational Behavior, 115, 103323.
Attig, C., Karp, A., & Franke, T. (2019). User diversity in the motivation for wearable activity tracking: A predictor for usage intensity? In S. Bagnara, R. Tartaglia, S. Albolino, T. Alexander, & Y. Fujita (Eds.), Proceedings of the 20th Congress of the International Ergonomics Association (iea 2018), Vol V: Human Simulation and Virtual Environments, Work with Computing Systems (wwcs), Process Control (Vol. 822, pp. 431–440). Springer International Publishing Ag.
Baas, M., Roskes, M., Koch, S., Cheng, Y., & De Dreu, C. K. W. (2019). Why social threat motivates malevolent creativity. Personality and Social Psychology Bulletin, 45(11), 1590–1602.
Bagby, M., Taylor, G. J., & Ryan, D. (1986). Toronto Alexithymia Scale: Relationship with personality and psychopathology measures. Psychotherapy and Psychosomatics, 45(4), 207–215.
Baker, D. A., & Algorta, G. P. (2016). The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies. Cyberpsychology, Behavior, and Social Networking, 19(11), 638–648.
Beck, A. T., Steer, R. A., & Brown, G. W. (2011). Beck Depression Inventory–II.
Bernstein, M. H., Wood, M. D., & Erickson, L. R. (2016). The effectiveness of message framing and temporal context on college student alcohol use and problems: A selective e-mail intervention. Alcohol and Alcoholism, 51(1), 106–116.
Bertrams, A., & Dickhäuser, O. (2012). Passionate thinkers feel better. Journal of Individual Differences, 33(2), 69–75.
Berzonsky, M. D., & Sullivan, C. (1992). Social-cognitive aspects of identity style: Need for Cognition, experiential openness, and introspection. Journal of Adolescent Research, 7(2), 140–155.
Blanchard, B. E., Littlefield, A. K., & Stevens, A. K. (2016). Thinking (or not) and drinking: Need for Cognition and alcohol use. Alcoholism-Clinical and Experimental Research, 40, 225A-225A.
Bless, H., Wänke, M., Bohner, G., Fellhauer, R. F., & Schwarz, N. (1994). Need for Cognition: Eine Skala zur Erfassung von Engagement und Freude bei Denkaufgaben. Zeitschrift für Sozialpsychologie, 25.
Boehm, J. K. (2018). Handbook of well-being (E. Diener, S. Oishi, & L. Tay, Eds.). DEF Publishers.
Booth-Butterfield, M., & Booth-Butterfield, S. (1990). Conceptualizing Affect as Information in Communication Production. Human Communication Research, 16(4), 451–476.
Bouckenooghe, D., Vanderheyden, K., Mestdagh, S., & van Laethem, S. (2007). Cognitive motivation correlates of coping style in decisional conflict. The Journal of Psychology: Interdisciplinary and Applied, 141(6), 605–626.
Braverman, J. (2008). Testimonials Versus Informational Persuasive Messages: The Moderating Effect of Delivery Mode and Personal Involvement. Communication Research, 35(5), 666–694.
Briñol, P., & Petty, R. E. (2022). Self-validation theory: An integrative framework for understanding when thoughts become consequential. Psychological Review, 129(2), 340–367.
Broyd, A., Ettinger, U., & Thoma, V. (2019). Thinking dispositions and cognitive reflection performance in schizotypy. Judgment and Decision Making, 14(1), 80–90.
Buck, K. D., Roe, D., Yanos, P., Buck, B., Fogley, R. L., Grant, M., Lubin, F., & Lysaker, P. H. (2013). Challenges to assisting with the recovery of personal identity and wellness for persons with serious mental illness: Considerations for mental health professionals. Psychosis, 5(2), 134–143.
Bye, D., & Pushkar, D. (2009). How need for cognition and perceived control are differentially linked to emotional outcomes in the transition to retirement. Motivation and Emotion, 33(3), 320–332.
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116–131.
Cacioppo, J. T., Petty, R. E., Feinstein, J. A., & Jarvis, W. B. G. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 119(2), 197–253.
Cacioppo, J. T., Petty, R. E., & Kao, C. F. (1984). The efficient assessment of need for cognition. Journal of Personality Assessment, 48(3), 306–307.
Capone, C., & Wood, M. D. (2009). Thinking about drinking: Need for cognition and readiness to change moderate the effects of brief alcohol interventions. Psychology of Addictive Behaviors: Journal of the Society of Psychologists in Addictive Behaviors, 23(4), 684–688.
Carey, K. B., Scott-Sheldon, L. A. J., Carey, M. P., & DeMartini, K. S. (2007). Individual-level interventions to reduce college student drinking: A meta-analytic review. Addictive Behaviors, 32(11), 2469–2494.
Carnevale, J. J., Inbar, Y., & Lerner, J. S. (2011). Individual differences in need for cognition and decision-making competence among leaders. Personality and Individual Differences, 51(3), 274–278.
Carney, J., & Robertson, C. (2018). People searching for meaning in their lives find literature more engaging. Review of General Psychology, 22(2), 199–209.
Cazan, A.-M., & Indreica, S. E. (2014). Need for Cognition and Approaches to Learning among University Students. Procedia - Social and Behavioral Sciences, 127, 134–138.
Chen, W.-L., & Chen, J.-H. (2019). Sleep deprivation and the development of leadership and need for cognition during the college years. Journal of Adolescence, 73(1), 95–99.
Cochran, W. G. (1954). Some methods for strengthening the common χ2 tests. Biometrics, 10(4), 417–451.
Cole, J. S., & Korkmaz, A. (2013). First-Year Students’ Psychological Well-Being and Need for Cognition: Are They Important Predictors of Academic Engagement? Journal of College Student Development, 54(6), 557–569.
Conner, M., Rhodes, R. E., Morris, B., McEachan, R., Lawton, R. (2011). Changing exercise through targeting affective or cognitive attitudes. Psychology Health, 26(2), 133–149.
Constantin, K., English, M. M., Mazmanian, D. (2018). Anxiety, Depression, and Procrastination Among Students: Rumination Plays a Larger Mediating Role than Worry. Journal of Rational-Emotive Cognitive-Behavior Therapy, 36(1), 15–27.
Cooke, P. J., Melchert, T. P., Connor, K. (2016). Measuring well-being. The Counseling Psychologist, 44(5), 730–757.
Coutinho, S. A., Woolery, L. M. (2004). The Need for Cognition and Life Satisfaction Among College Students. College Student Journal, 38(2), 203–206.
Cramer, R. J., Bryson, C. N., Gardner, B. O., Webber, W. B. (2016). Can preferences in information processing aid in understanding suicide risk among emerging adults? Death Studies, 40(6), 383–391.
Cramer, R. J., Franks, M., Cunningham, C. A., Bryan, C. J. (2020). Preferences in information processing: Understanding suicidal thoughts and behaviors among active duty military service members. Archives of Suicide Research, 26(1), 169–186.
Cramer, R. J., Langhinrichsen-Rohling, J., Kaniuka, A. R., Wilsey, C. N., Mennicke, A., Wright, S., Montanaro, E., Bowling, J., Heron, K. E. (2020). Preferences in information processing, marginalized identity, and non-monogamy: Understanding factors in suicide-related behavior among members of the alternative sexuality community. International Journal of Environmental Research and Public Health, 17(9), 3233.
Cramer, R. J., Rasmussen, S., Webber, W. B., Sime, V. L., Haile, C., McFadden, C., McManus, M. C. (2019). Preferences in information processing and suicide: Results from a young adult health survey in the United Kingdom. International Journal of Social Psychiatry, 65(1), 46–55.
Crawford, J. R., Henry, J. D. (2004). The Positive and Negative Affect Schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43(3), 245–265.
Curşeu, P. L., de Jong, J. P. (2017). Bridging social circles: Need for Cognition, prejudicial judgments, and personal social network characteristics. Frontiers in Psychology, 8.
Czuchry, M., Dansereau, D. F. (2004). The importance of need for cognition and educational experience in enhanced and standard substance abuse treatment. Journal of Psychoactive Drugs, 36(2), 243–251.
Darvishi, M., Seif, M. H., Sarmadi, M. R., Farajollahi, M. (2020). An investigation into the Factors Affecting Perceived Enjoyment of Learning in Augmented Reality: A Path Analysis. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 11(4), 224–235.
de Holanda Coelho, G. L., Hanel, P. H. P., Wolf, L. J. (2018). The very efficient assessment of Need for Cognition: Developing a six-item version. Assessment, 27(8), 1870–1885.
De Pelsmacker, P., Lewi, M., Cauberghe, V. (2017). The effect of personal characteristics, perceived threat, efficacy and breast cancer anxiety on breast cancer screening activation. Healthcare, 5(4), 65.
Denovan, A., Dagnall, N., Drinkwater, K., Parker, A., Neave, N. (2020). Conspiracist beliefs, intuitive thinking, and schizotypal facets: A further evaluation. Applied Cognitive Psychology, 34(6), 1394–1405.
Diener, Ed, Emmons, R. A., Larsen, R. J., Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49(1), 71–75.
Diener, Ed, Lucas, R. R. (1999). Well-being: The foundations of hedonic psychology (D. Kahneman, E. Diener, N. Schwarz, Eds.). Russell Sage Foundation.
Dik, B. J., Hansen, J.-I. C. (2008). Following passionate interests to well-being. Journal of Career Assessment, 16(1), 86–100.
Dodge, R., Daly, A., Huyton, J., Sanders, L. (2012). The challenge of defining wellbeing. International Journal of Wellbeing, 2(3), 222–235.
Double, K. S., Birney, D. P. (2016). The effects of personality and metacognitive beliefs on cognitive training adherence and performance. Personality and Individual Differences, 102, 7–12.
Duval, S., Tweedie, R. (2000). Trim and Fill: A Simple Funnel-Plot–Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis. Biometrics, 56(2), 455–463.
Dvir-Gvirsman, S. (2019). I like what I see: Studying the influence of popularity cues on attention allocation and news selection. Information, Communication Society, 22(2), 286–305.
Enns, M. W., Cox, B. J. (1997). Personality dimensions and depression: Review and commentary. The Canadian Journal of Psychiatry, 42(3), 274–284.
Epstein, S., Pacini, R., Denes-Raj, V., Heier, H. (1996). Individual differences in intuitive–experiential and analytical–rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390–405.
Erikson, E. H. (1994). Identity and the Life Cycle. W. W. Norton.
Falces, C., Briñol, P., Sierra, B., Becerra, A., Alier, E. (2001). Validación de la escala de necesidad de cognición y su aplicación al estudio del cambio de actitudes [Validation of the Need for Cognition Scale and its application to attitude change]. Psicothema, 13(4), 622–628.
Fenigstein, A., Scheier, M. F., Buss, A. H. (1975). Public and private self-consciousness: Assessment and theory. Journal of Consulting and Clinical Psychology, 43(4), 522–527.
Fine, S., Nevo, B. (2008). Too smart for their own good? A study of perceived cognitive overqualification in the workforce. The International Journal of Human Resource Management, 19(2), 346–355.
Finkenauer, C., Engels, R. C. M. E., Baumeister, R. F. (2005). Parenting behaviour and adolescent behavioural and emotional problems: The role of self-control. International Journal of Behavioral Development, 29(1), 58–69.
Fleischhauer, M., Enge, S., Brocke, B., Ullrich, J., Strobel, A., Strobel, A. (2010). Same or different? Clarifying the relationship of need for cognition to personality and intelligence. Personality Social Psychology Bulletin, 36(1), 82–96.
Fletcher, G. J. O., Danilovics, P., Fernandez, G., Peterson, D., Reeder, G. D. (1986). Attributional complexity: An individual differences measure. Journal of Personality and Social Psychology, 51(4), 875–884.
Frison, E., Eggermont, S. (2016). Exploring the Relationships Between Different Types of Facebook Use, Perceived Online Social Support, and Adolescents’ Depressed Mood. Social Science Computer Review, 34(2), 153–171.
Gailliot, M. T., Schmeichel, B. J., Baumeister, R. F. (2006). Self-regulatory processes defend against the threat of death: Effects of self-control depletion and trait self-control on thoughts and fears of dying. Journal of Personality and Social Psychology, 91(1), 49–62.
Gallagher, K. M., Updegraff, J. A. (2011). When ‘fit’ leads to fit, and when ‘fit’ leads to fat: How message framing and intrinsicvs. extrinsic exercise outcomes interact in promoting physical activity. Psychology Health, 26(7), 819–834.
Gallagher, V. C. (2012). Managing resources and need for cognition: Impact on depressed mood at work. Personality and Individual Differences, 53(4), 534–537.
Gallivan, N. (2020). Behavior feedback and Need for Cognition: Factors affecting coffee beverage consumption [Thesis].
Gärtner, A., Grass, J., Wolff, M., Goschke, T., Strobel, A., Strobel, A. (2021). No relation of Need for Cognition to basic executive functions. Journal of Personality, 89(6), 1113–1125.
Gauthier, K. J., Christopher, A. N., Walter, M. I., Mourad, R., Marek, P. (2006). Religiosity, religious doubt, and the Need for Cognition: Their interactive relationship with life satisfaction. Journal of Happiness Studies, 7(2), 139–154.
Ghorbani, N., Davison, H. K., Bing, M. N., Watson, P. J., Krauss, S. W. (2004). Private Self-Consciousness factors: Relationships with Need for Cognition, locus of control, and obsessive thinking in Iran and the United States. Journal of Social Psychology, 144(4), 359–372.
Gignac, G. E., Szodorai, E. T. (2016). Effect size guidelines for individual differences researchers. Personality and Individual Differences, 102, 74–78.
Grandi, B., Cardinali, M. G., Bellini, S. (2020). Health and self-control: Promoting unconscious healthy food choices inside the store. International Journal of Retail Distribution Management, 48(3), 229–243.
Grass, J., John, N., Strobel, A. (2018). The joy of thinking as the key to success? The importance of Need for Cognition for subjective experience and achievement in academic studies. Zeitschrift für Pädagogische Psychologie, 32(3), 145–154.
Grass, J., Krieger, F., Paulus, P., Greiff, S., Strobel, A., Strobel, A. (2019). Thinking in action: Need for Cognition predicts Self-Control together with Action Orientation. PLOS ONE, 14(8), e0220282.
Grass, J., Strobel, A., Strobel, A. (2017). Cognitive investments in academic success: The role of Need for Cognition at university. Frontiers in Psychology, 8.
Green, M. C., Jenkins, K. M. (2020). Need for Cognition, Transportability, and engagement with interactive narratives. Games for Health Journal, 9(3), 182–186.
Green, M. C., Kaufman, G., Flanagan, M., Fitzgerald, K. (2017). Self-esteem and public self-consciousness moderate the emotional impact of expressive writing about experiences with bias. Personality and Individual Differences, 116, 212–215.
Greenblatt, M., Becerra, R. M., Serafetinides, E. A. (1982). Social networks and mental health: On overview. American Journal of Psychiatry, 139(8), 977–984.
Gülgöz, S. (2001). Need for Cognition and cognitive performance from a cross-cultural perspective: Examples of academic success and solving anagrams. The Journal of Psychology, 135(1), 100–112.
Hadj-Abo, A., Enge, S., Rose, J., Kunte, H., Fleischhauer, M. (2020). Individual differences in impulsivity and need for cognition as potential risk or resilience factors of diabetes self-management and glycemic control. Plos One, 15(1), e0227995.
Harman, J. L. (2011). Individual differences in Need for Cognition and decision making in the Iowa Gambling Task. Personality and Individual Differences, 51(2), 112–116.
Harrer, M., Cuijpers, P., Furukawa, T. A., Ebert, D. D. (2021). Doing meta-analysis with R: A hands-on guide. Chapman Hall/CRC Press.
Haug, S., Meyer, C., Ulbricht, S., Gross, B., Rumpf, H.-J., John, U. (2010). Need for Cognition as a predictor and a moderator of outcome in a tailored letters smoking cessation intervention. Health Psychology, 29(4), 367–373.
Haugtvedt, C. P., Petty, R. E. (1992). Personality and persuasion: Need for Cognition moderates the persistence and resistance of attitude changes. Journal of Personality and Social Psychology, 63(2), 308–319.
Hay, J. L., Schofield, E., Kiviniemi, M., Waters, E. A., Chen, X., Kaphingst, K., Li, Y., Orom, H. (2020). Examining strategies for addressing high levels of ‘I don’t know’ responding to risk perception questions for colorectal cancer and diabetes: An experimental investigation. Psychology Health, 36(7), 862–878.
Henning, B., Vorderer, P. (2001). Psychological escapism: Predicting the amount of television viewing by Need for Cognition. Journal of Communication, 51(1), 100–120.
Henry, J. D., Crawford, J. R. (2005). The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 44(Pt 2), 227–239.
Heppner, P. P., Reeder, B. L., Larson, L. M. (1983). Cognitive variables associated with personal problem-solving appraisal: Implications for counseling. Journal of Counseling Psychology, 30(4), 537–545.
Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., Welch, V. A. (Eds.). (2019). Cochrane handbook for systematic reviews of interventions (2nd ed.). Wiley.
Higgins, J. P. T., Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21(11), 1539–1558.
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., Altman, D. G. (2003). Measuring inconsistency in meta-analyses. BMJ (Clinical Research Ed.), 327(7414), 557–560.
Hittner, J. B. (2004). Alcohol use among american college students in relation to need for cognition and expectations of alcohol’s effects on cognition. Current Psychology, 23(2), 173–187.
Hohmann, L. A., Garza, K. B. (2022). The moderating power of impulsivity: A systematic literature review examining the Theory of Planned Behavior. Pharmacy, 10(4), 85–104.
Holch, P., Marwood, J. R. (2020). EHealth literacy in UK teenagers and young adults: Exploration of predictors and factor structure of the eHealth Literacy Scale (eHEALS). JMIR Formative Research, 4(9), e14450.
Homan, P., Reddan, M. C., Brosch, T., Koenigsberg, H. W., Schiller, D. (2017). Aberrant link between empathy and social attribution style in borderline personality disorder. Journal of Psychiatric Research, 94, 163–171.
Horcajo, J., Santos, D., Guyer, J. J., Moreno, L. (2019). Changing attitudes and intentions related to doping: An analysis of individual differences in Need for Cognition. Journal of Sports Sciences, 37(24), 2835–2843.
Hull, C. L. (1943). Principles of behaviour: An introduction to behavior theory. Appleton-Century-Crofts.
Huta, V. (2013). Oxford handbook of happiness (S. David, I. Boniwell, A. C. Ayers, Eds.). Oxford University Press.
Ingendahl, M., Hummel, D., Maedche, A., Vogel, T. (2020). Who can be nudged? Examining nudging effectiveness in the context of Need for Cognition and Need for Uniqueness. Journal of Consumer Behaviour, 20(2), 324–336.
Inzlicht, M., Shenhav, A., Olivola, C. Y. (2018). The Effort Paradox: Effort is both costly and valued. Trends in Cognitive Sciences, 22(4), 337–349.
Jennings, J. G., Galupo, M. P., Cartwright, K. B. (2009). The role of postformal cognitive development in death acceptance. Journal of Adult Development, 16(3), 166–172.
Johnson, G. J., Johnson, W. R. (2000). Perceived overqualification and dimensions of job satisfaction: A longitudinal analysis. The Journal of Psychology, 134(5), 537–555.
Kahneman, D., Diener, E., Schwarz, N. (1999). Well-being: The foundations of hedonic psychology. Russell Sage Foundation.
Kao, C. (1994). The concept and measurement of Need for Cognition. Chinese Journal of Psychology, 36(1), 1–20.
Karagiannopoulou, E., Milienos, F. S., Rentzios, C. (2020). Grouping learning approaches and emotional factors to predict students’ academic progress. International Journal of School Educational Psychology, 10(2), 258–275.
Kardash, C. A. M., Noel, L. K. (2000). How organizational signals, Need for Cognition, and verbal ability affect text recall and recognition. Contemporary Educational Psychology, 25(3), 317–331.
Kelders, S. M., Bohlmeijer, E. T., Gemert-Pijnen, J. E. V. (2013). Participants, usage, and use patterns of a web-based intervention for the prevention of depression within a randomized controlled trial. Journal of Medical Internet Research, 15(8), e172.
Kelly, K. M., Shedlosky-Shoemaker, R., Porter, K., DeSimone, P., Andrykowski, M. (2010). Cancer recurrence worry, risk perception, and informational-coping styles among Appalachian cancer survivors. Journal of Psychosocial Oncology, 29(1), 1–18.
Kessler, E. D., Braasch, J. L. G., Kardash, C. M. (2019). Individual differences in revising (and maintaining) accurate and inaccurate beliefs about childhood vaccinations. Discourse Processes, 56(5–6), 415–428.
Kim, I., Feng, B., Jang, J., Wang, B. (2019). Reassessing the integrated model of advice-giving in supportive interactions: The moderating roles of Need for Cognition and communication styles. Social Influence, 14(1), 14–24.
Klaczynski, P. A., Fauth, J. M. (1996). Intellectual ability, rationality, and intuitiveness as predictors of warranted and unwarranted optimism for future life events. Journal of Youth and Adolescence, 25(6), 755–773.
Knobloch-Westerwick, S., Mothes, C., Polavin, N. (2020). Confirmation bias, ingroup bias, and negativity bias in selective exposure to political information. Communication Research, 47(1), 104–124.
Kobbeltvedt, T., Brun, W., Laberg, J. C. (2005). Cognitive processes in planning and judgements under sleep deprivation and time pressure. Organizational Behavior and Human Decision Processes, 98(1), 1–14.
Krezmien, E., Wanzer, M. B., Servoss, T., LaBelle, S. (2011). The role of direct-to-consumer pharmaceutical advertisements and individual differences in getting people to talk to physicians. Journal of Health Communication, 16(8), 831–848.
Kührt, C., Pannasch, S., Kiebel, S. J., Strobel, A. (2021). Dispositional individual differences in cognitive effort investment: Establishing the core construct. BMC Psychology, 9(1), 10.
La Fauci, V., Squeri, R., Spataro, P., Genovese, C., Laudani, N., Alessi, V. (2019). Young people, young adults and binge drinking. Journal of Preventive Medicine and Hygiene, 60(4), E376–E385.
Lahey, B. B. (2009). Public health significance of neuroticism. American Psychologist, 64(4), 241–256.
Latimer, A. E., Williams-Piehota, P., Cox, A., Katulak, N. A., Salovey, P., Mowad, L. (2007). Encouraging Cancer Patients to Talk to Their Physicians About Clinical Trials: Considering Patients’ Information Needs1. Journal of Applied Biobehavioral Research, 12(3–4), 178–195.
Lavender, A., Watkins, E. (2004). Rumination and future thinking in depression. British Journal of Clinical Psychology, 43(2), 129–142.
Laws, M. B., Lee, Y., Rogers, W. S., Taubin, T., Wilson, I. B. (2020). An instrument to assess HIV-related knowledge and adjustment to HIV+ status, and their association with anti-retroviral adherence. Plos One, 15(6), e0227722.
Lecky, P., Taylor, J. F. A. (1945). Self-consistency, a theory of personality. Island Press.
Leone, C., Hawkins, L. B., Bright, M. (2019). Minimizing mistreatment by female adults: The influence of gender-based social categories and personality differences on attitudes about child sexual abuse. Journal of Psychology, 153(4), 361–382.
Lin, H.-C., Shih, L.-C., Lin, H.-M. (2017). The influence of consumers’ self-perceived health status and Need for Cognition on food-product evaluation. British Food Journal, 119(2), 242–252.
Lins, S., Aquino, S. (2020). Development and initial psychometric properties of a panic buying scale during COVID-19 pandemic. Heliyon, 6(9), e04746.
Linvill, D. L., Mazer, J. P., Boatwright, B. C. (2016). Need for Cognition as a mediating variable between aggressive communication traits and tolerance for disagreement. Communication Research Reports, 33(4), 363–369.
Littrell, S., Fugelsang, J., Risko, E. F. (2020). Overconfidently underthinking: Narcissism negatively predicts cognitive reflection. Thinking Reasoning, 26(3), 352–380.
Liu, B., Yang, L., Xiang, S. (2020). Determining the factors affecting learning motivation of Master candidates of economic management based on Need for Cognition. Revista Argentina de Clínica Psicológica.
Liu, Q., Nesbit, J. C. (2023). The relation between Need for Cognition and academic achievement: A meta-analysis. Review of Educational Research, 003465432311604.
Loose, T., Vasquez-Echeverría, A., Álvarez-Núñez, L. (2023). Spanish version of need for cognition scale: Evidence of reliability, validity and factorial invariance of the very efficient short-form. Current Psychology, 42(17), 14440–14451.
Maio, G. R., Esses, V. M. (2001). The Need for Affect: Individual differences in the motivation to approach or avoid emotions. Journal of Personality, 69(4), 583–614.
Maki, K. G., Feeley, T. H. (2021). Influencing HIV Testing Intentions: Comparing Narrative and Statistical Messages. Communication Studies, 72(2), 178–194.
Maloney, E. A., Retanal, F. (2020). Higher math anxious people have a lower Need for Cognition and are less reflective in their thinking. Acta Psychologica, 202, 102939.
Maschio, J. (2018). The Need for Cognition and Critical Thinking Skills and Depressive Symptoms in College Students [Walden University].
Maslach, C., Jackson, S. E., Leiter, M. P. (1997). Maslach Burnout Inventory: Third edition. In Evaluating Stress: A Book of Resources. Scarecrow Education.
McElroy, T., Dickinson, D. L., Stroh, N., Dickinson, C. A. (2016). The physical sacrifice of thinking: Investigating the relationship between thinking and physical activity in everyday life. Journal of Health Psychology, 21(8), 1750–1757.
McMath, B. F., Prentice-Dunn, S. (2005). Protection Motivation Theory and skin cancer risk: The role of individual differences in responses to persuasive appeals. Journal of Applied Social Psychology, 35(3), 621–643.
Meertens, R. M., Lion, R. (2008). Measuring an individual’s tendency to take risks: The Risk Propensity Scale. Journal of Applied Social Psychology, 38(6), 1506–1520.
Meyer, T. J., Miller, M. L., Metzger, R. L., Borkovec, T. D. (1990). Development and validation of the Penn State Worry Questionnaire. Behaviour Research and Therapy, 28(6), 487–495.
Mouneyrac, A., Lemercier, C., Floch, V. L., Challet-Bouju, G., Moreau, A., Jacques, C., Giroux, I. (2018). Cognitive characteristics of strategic and non-strategic gamblers. Journal of Gambling Studies, 34(1), 199–208.
Naderi, Z., Bakhtiari, S., Momennasab, M., Abootalebi, M., Mirzaei, T. (2018). Prediction of academic burnout and academic performance based on the need for cognition and general self-efficacy: A cross-sectional analytical study. Latinoamericana de Hipertensión, 13(6).
Nair, K. U., Ramnarayan, S. (2000). Individual differences in Need for Cognition and complex problem solving. Journal of Research in Personality, 34(3), 305–328.
Nazir, T., Thabassum, L. (2022). The role of socio-demographics, family, and peer factors in adolescent alcohol behaviors. International Journal of English Literature and Social Sciences, 7(2), 208–218.
Nishiguchi, Y., Mori, M., Tanno, Y. (2018). Need for Cognition promotes adaptive style of self-focusing with the mediation of Effortful Control. Japanese Psychological Research, 60(1), 54–61.
Nishiguchi, Y., Takano, K., Tanno, Y. (2016). The Need for Cognition mediates and moderates the association between depressive symptoms and impaired Effortful Control. Psychiatry Research, 241, 8–13.
Njus, D., Johnson, D. R. (2008). Need for Cognition as a predictor of psychosocial identity development. The Journal of Psychology, 142(6), 645–655.
Nolen-Hoeksema, S., Wisco, B. E., Lyubomirsky, S. (2008). Rethinking Rumination. Perspectives on Psychological Science, 3(5), 400–424.
Noone, C., Hogan, M. J. (2018). Improvements in critical thinking performance following mindfulness meditation depend on thinking dispositions. Mindfulness, 9(2), 461–473.
Nowlin, E., Walker, D., Deeter-Schmelz, D. R., Haas, A. (2017). Emotion in sales performance: Affective orientation and Need for Cognition and the mediating role of motivation to work. Journal of Business Industrial Marketing, 33(1), 107–116.
Occa, A., Kim, S., Carcioppolo, N., Morgan, S. E., Anderson, D. (2020). A comparison of metaphor modality and appeals in the context of skin cancer prevention. Journal of Health Communication, 25(1), 12–22.
Oh, S., Meyerowitz, B. E., Perez, M. A., Thornton, A. A. (2007). Need for Cognition and psychosocial adjustment in prostate cancer patients and partners. Journal of Psychosocial Oncology, 25(1), 1–19.
Ohrnberger, J., Fichera, E., Sutton, M. (2017). The relationship between physical and mental health: A mediation analysis. Social Science Medicine, 195, 42–49.
Olson, K., Camp, C., Fuller, D. (1984). Curiosity and Need for Cognition. Psychological Reports, 54(1), 71–74.
Ormel, J., Jeronimus, B. F., Kotov, R., Riese, H., Bos, E. H., Hankin, B., Rosmalen, J. G. M., Oldehinkel, A. J. (2013). Neuroticism and common mental disorders: Meaning and utility of a complex relationship. Clinical Psychology Review, 33(5), 686–697.
Osberg, T. M. (1987). The convergent and discriminant validity of the Need for Cognition Scale. Journal of Personality Assessment, 51(3), 441–450.
Osberg, T. M., Poland, D., Aguayo, G., MacDougall, S. (2008). The Irrational Food Beliefs Scale: Development and validation. Eating Behaviors, 9(1), 25–40.
Otaghi, M., Sayehmiri, K., Valizadeh, R., Tavan, H. (2019). Correlation between happiness and academic achievement in Iranian students: A meta-analysis letter. Shiraz E-Medical Journal, 21(3).
Ozer, B. U., O’Callaghan, J., Bokszczanin, A., Ederer, E., Essau, C. (2014). Dynamic interplay of depression, perfectionism and self-regulation on procrastination. British Journal of Guidance Counselling, 42(3), 309–319.
Pan, Y., Shang, Y., Malika, R. (2020). Enhancing creativity in organizations: The role of the need for cognition. Management Decision, 59(9), 2057–2076.
Park, G., Lim, B.-C., Oh, H. S. (2019). Why being bored might not be a bad thing after all. Academy of Management Discoveries, 5(1), 78–92.
Pearlin, L. I., Nguyen, K. B., Schieman, S., Milkie, M. A. (2007). The life-course origins of mastery among older people. Journal of Health and Social Behavior, 48(2), 164–179.
Peters, J. L., Sutton, A. J., Jones, D. R., Abrams, K. R., Rushton, L. (2006). Comparison of two methods to detect publication bias in meta-analysis. JAMA, 295(6), 676–680.
Pilarska, A. (2015). Contextualized self-views and sense of identity. Personality and Individual Differences, 86, 326–331.
Pilarska, A. (2017). Contributions of cognitive-motivational factors to the sense of identity. Current Psychology, 36(3), 468–482.
Popoviciu, S. A., Barbu, A., Costea, D., Culda, L., Culda, S. (2011). Students’ desire to engage in cognitive activities, family of origin characteristics and Need for Cognition scores. Problems of Education in the 21st Century, 33(1), 62–72.
Priya, P., Mutha, A., Purohit, M., Yadav, S., Bansal, S. (2023). Risk factors associated with HIV infection among persons attending ICTC and PPTCT centre of a tertiary care hospital of central India. Global Journal for Research Analysis, 12(3), 57–59.
Prohaska, V., Celestino, D., Dangleben, T., Sanchez, P., Sandoval, A. (2018). Assessing ‘clutter’ and related constructs with a non-white, urban sample. Current Psychology, 37(2), 432–435.
R Core Team. (2021). R: A language and environment for statistical computing (4.1.1). R Foundation for Statistical Computing.
Rack, J. J., Burleson, B. R., Bodie, G. D., Holmstrom, A. J., Servaty-Seib, H. (2008). Bereaved adults’ evaluations of grief management messages: Effects of message person centeredness, recipient individual differences, and contextual factors. Death Studies, 32(5), 399–427.
Reeves, A., Watson, P., Ramsey, A., Morris, R. (1995). Private Self-Consciousness factors, Need for Cognition, and depression. Journal of Social Behavior Personality, 10, 431–443.
Riley, K. E., Hay, J. L., Waters, E. A., Biddle, C., Schofield, E., Li, Y., Orom, H., Kiviniemi, M. T. (2019). Lay beliefs about risk: Relation to risk behaviors and to probabilistic risk perceptions. Journal of Behavioral Medicine, 42(6), 1062–1072.
Rogers, C. R. (1959). A Theory of Therapy, Personality, and Interpersonal Relationships: As Developed in the Client-Centered Framework. In S. Koch (Ed.), Psychology: A Study of Science. Formulations of the Person and the Social Context (Vol. 3, pp. 184–256). McGraw-Hill.
Rogers, P., Fisk, J. E., Lowrie, E. (2018). Paranormal belief, thinking style preference and susceptibility to confirmatory conjunction errors. Consciousness and Cognition, 65, 182–196.
Rosen, C. C., Gabriel, A. S., Lee, H. W., Koopman, J., Johnson, R. E. (2020). When lending an ear turns into mistreatment: An episodic examination of leader mistreatment in response to venting at work. Personnel Psychology, 74(1), 175–195.
RStudio Team. (2021). RStudio: Integrated Development for R (2021.9.0.351). RStudio, PBC.
Ruiter, R. A. C., Verplanken, B., De Cremer, D., Kok, G. (2004). Danger and fear control in response to fear appeals: The role of Need for Cognition. Basic and Applied Social Psychology, 26(1), 13–24.
Ryan, R. M., Deci, E. L. (2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual Review of Psychology, 52(1), 141–166.
Scheffel, C., Graupner, S.-T., Gärtner, A., Zerna, J., Strobel, A., Dörfel, D. (2021). Effort beats effectiveness in emotion regulation choice: Differences between suppression and distancing in subjective and physiological measures. Psychophysiology, 58(11), e13908.
Schei, V., Sverdrup, T. E., Andvik, E. (2020). “Let’s get out of here!”: Cognitive motivation and maximizing help teams solving an escape room. Frontiers in Psychology, 11.
See, Y. H. M., Petty, R. E., Evans, L. M. (2009). The impact of perceived message complexity and need for cognition on information processing and attitudes. Journal of Research in Personality, 43(5), 880–889.
Sevincer, A. T., Mehl, P. J., Oettingen, G. (2017). Well self-regulated people use mental contrasting. Social Psychology, 48(6), 348–364.
Shadel, W. G., Lerman, C., Cappella, J., Strasser, A. A., Pinto, A., Hornik, R. (2006). Evaluating smokers’ reactions to advertising for new lower nicotine quest cigarettes. Psychology of Addictive Behaviors, 20(1), 80–84.
Shi, J., Chen, Z., Tian, M. (2010). Internet self-efficacy, the Need for Cognition, and Sensation Seeking as predictors of problematic use of the internet. Cyberpsychology, Behavior, and Social Networking, 14(4), 231–234.
Shim, H., Kim, K. J. (2017). An exploration of the motivations for binge-watching and the role of individual differences. Computers in Human Behavior, 82, 94–100.
Shim, H., Lim, S., Jung, E. E., Shin, E. (2018). I hate binge-watching but I can’t help doing it: The moderating effect of immediate gratification and Need for Cognition on binge-watching attitude-behavior relation. Telematics and Informatics, 35(7), 1971–1979.
Singh, S., Saini, S. (2007). HIV risk perception in relation to peer pressure and drug abuse behavior among adolescents. Indian Journal of Sexually Transmitted Diseases and AIDS, 28(1), 53–54.
Stanley, T. D. (2017). Limitations of PET-PEESE and other meta-analysis methods. Social Psychological and Personality Science, 8(5), 581–591.
Stevens, E. M., Wetter, D. W., Vidrine, D. J., Hoover, D. S., Frank-Pearce, S. G., Nguyen, N., Li, Y., Waters, A. J., Meade, C. D., Wagener, T. L., Vidrine, J. I. (2019). Enhancing smoking risk communications: The influence of Need for Cognition. American Journal of Health Behavior, 43(5), 950–962.
Stewart, S. L. K., Kirkham, J. A. (2020). Predictors of individual differences in emerging adult Theory of Mind. Emerging Adulthood, 10(2), 558–565.
Strobel, A. (2022, March 14). Looking for unpublished datasets including associations of NFC and any indicator (see below) of well-being to include in [Tweet, attached image]. Twitter.
Strobel, A., Anacker, K., Strobel, A. (2017). Cognitive engagement mediates the relationship between positive life events and positive emotionality. Frontiers in Psychology, 8.
Strobel, A., Behnke, A., Gärtner, A., Strobel, A. (2019). The interplay of intelligence and need for cognition in predicting school grades: A retrospective study. Personality and Individual Differences, 144, 147–152.
Strobel, A., Strobel, A., Enge, S., Fleischhauer, M., Reif, A., Lesch, K.-P., Anacker, K. (2018). Intellectual investment, dopaminergic gene variation, and life events: A critical examination. Personality Neuroscience, 1.
Tabbodi, M. L., Rahgozar, H., Abadi, M. M. M. (2015). The relationship between happiness and academic achievements. European Online Journal of Natural and Social Sciences, 4, 241–246.
Takano, K., Tanno, Y. (2009). Self-rumination, self-reflection, and depression: Self-rumination counteracts the adaptive effect of self-reflection. Behaviour Research and Therapy, 47(3), 260–264.
Tamir, M., Ford, B. Q. (2012). Should people pursue feelings that feel good or feelings that do good? Emotional preferences and well-being. Emotion, 12(5), 1061–1070.
Tamir, M., Schwartz, S. H., Oishi, S., Kim, M. Y. (2017). The secret to happiness: Feeling good or feeling right? Journal of Experimental Psychology: General, 146(10), 1448–1459.
Tan, T. Y., Jain, M., Obaid, T., Nesbit, J. C. (2020). What can completion time of quizzes tell us about students’ motivations and learning strategies? Journal of Computing in Higher Education, 32(2), 389–405.
Tangney, J. P., Baumeister, R. F., Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271–324.
The WHOQOL Group. (1998). The World Health Organization quality of life assessment (WHOQOL): Development and general psychometric properties. Social Science Medicine, 46(12), 1569–1585.
Thomas, C. L., Kirby, L. A. J. (2020). Situational interest helps correct misconceptions: An investigation of conceptual change in university students. Instructional Science, 48(3), 223–241.
Thomas, R. L., Millar, M. G. (2008). The impact of failing to give an apology and the Need for Cognition on anger. Current Psychology, 27(2), 126–134.
Thompson, E. P., Chaiken, S., Hazlewood, J. D. (1993). Need for Cognition and Desire for Control as Moderators of Extrinsic Reward Effects—A Person X Situation Approach to the Study of Intrinsic Motivation. Journal of Personality and Social Psychology, 64(6), 987–999.
Thompson, M. M., Zanna, M. P. (1995). The conflicted individual—Personality-based and domain-specific antecedents of ambivalent social-attitudes. Journal of Personality, 63(2), 259–288.
Tinlin, R. M., Gotts, Z. M., Dunn, K. I., Ritchie, M. (2021). ‘Riding an emotional rollercoaster’: A qualitative exploration of the psychological and social impact of the Covid-19 pandemic on UK residents. Clinical Psychology Forum, 1(337), 11–18.
Tomljenovic, H., Bubic, A., Erceg, N. (2020). It just doesn’t feel right–The relevance of emotions and intuition for parental vaccine conspiracy beliefs and vaccination uptake. Psychology Health, 35(5), 538–554.
Trapnell, P. D., Campbell, J. D. (1999). Private self-consciousness and the five-factor model of personality: Distinguishing rumination from reflection. Journal of Personality and Social Psychology, 76(2), 284–304.
Trogrlic, A., Vasic, A. (2009). The convergent and discriminant validity of the need for cognition. Psihologija, 42(2), 173–186.
Tuncdogan, A., Ar, A. A. (2018). Distal and proximal predictors of food personality: An exploratory study on food neophilia. Personality and Individual Differences, 129, 171–174.
Vainio, A. (2019). How consumers of meat-based and plant-based diets attend to scientific and commercial information sources: Eating motives, the Need for Cognition and ability to evaluate information. Appetite, 138, 72–79.
Vannucci, M., Chiorri, C. (2018). Individual differences in self-consciousness and mind wandering: Further evidence for a dissociation between spontaneous and deliberate mind wandering. Personality and Individual Differences, 121, 57–61.
Vaughan-Johnston, T. I., Jackowich, R. A., Hudson, C. C., De France, K., Hollenstein, T., Jacobson, J. A. (2020). The role of individual differences in emotion regulation efficacy. Journal of Research in Personality, 84, 103904.
Verhaeghen, P., Joormann, J., Aikman, S. N. (2014). Creativity, mood, and the examined life: Self-reflective rumination boosts creativity, brooding breeds dysphoria. Psychology of Aesthetics, Creativity, and the Arts, 8(2), 211–218.
Vidrine, J. I., Simmons, V. N., Brandon, T. H. (2007). Construction of smoking-relevant risk perceptions among college students: The influence of Need for Cognition and message content. Journal of Applied Social Psychology, 37(1), 91–114.
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48.
Vogt, R. L., Zheng, A., Briley, D. A., Malanchini, M., Harden, K. P., Tucker-Drob, E. M. (2022). Genetic and Environmental Factors of Non-Ability-Based Confidence. Social Psychological and Personality Science, 13(3), 734–746.
Waterman, A. S. (1993). Two conceptions of happiness: Contrasts of personal expressiveness (eudaimonia) and hedonic enjoyment. Journal of Personality and Social Psychology, 64(4), 678–691.
Watt, J. D., Blanchard, M. J. (1994). Boredom proneness and the Need for Cognition. Journal of Research in Personality, 28(1), 44–51.
Weary, G., Edwards, J. A. (1994). Individual differences in causal uncertainty. Journal of Personality and Social Psychology, 67(2), 308–318.
Williams-Piehota, P., Pizarro, J., Silvera, S. A. N., Mowad, L., Salovey, P. (2006). Need for Cognition and message complexity in motivating fruit and vegetable intake among callers to the cancer information service. Health Communication, 19(1), 75–84.
Wolf, L. J., Hecker, U. von, Maio, G. R. (2017). Affective and cognitive orientations in intergroup perception. Personality and Social Psychology Bulletin, 43(6), 828–844.
World Health Organization (Ed.). (2016). The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. World Health Organization.
Wycoff, E. B. (1992). Apprehension about communication and the Need for Cognition. Perceptual and Motor Skills, 75(3_suppl), 1225–1226.
Xu, P., Cheng, J. (2021). Individual differences in social distancing and mask-wearing in the pandemic of COVID-19: The role of need for cognition, self-control and risk attitude. Personality and Individual Differences, 175, 110706.
Yan, X., Otto, A. R. (2020). Cognitive effort investment and opportunity costs in strategic decision-making: An individual differences examination. Personality and Individual Differences, 167, 110283.
Yazdani, N., Siedlecki, K. L. (2021). Mediators of the Relationship Between Cognition and Subjective Well-Being. Journal of Happiness Studies, 22(7), 3091–3109.
Zadelaar, J. N., Dekkers, T. J., Huizenga, H. M. (2020). The association between risky decision making and attention-deficit/hyperactivity disorder symptoms: A preregistered assessment of Need for Cognition as underlying mechanism. Journal of Behavioral Decision Making, 33(5), 579–592.
Zerna, J., Engelmann, N., Strobel, A., Strobel, A. (2022). Need for Cognition and burnout in teachers – A replication and extension study. Health Psychology Open, 9(2), 205510292211396.
Zerna, J., Scheffel, C., Kührt, C., Strobel, A. (2023). Need for Cognition is associated with a preference for higher task load in effort discounting. Scientific Reports, 13(1), 19501.
Zhong, B., Hardin, M., Sun, T. (2011). Less effortful thinking leads to more social networking? The associations between the use of social network sites and personality traits. Computers in Human Behavior, 27(3), 1265–1271.
Zhou, M. (2019). The role of personality traits and Need for Cognition in active procrastination. Acta Psychologica, 199, 102883.
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