The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature

The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature. Scott Barry Kaufman, David Bryce Yaden, Elizabeth Hyde and Eli Tsukayama. Front. Psychol., March 12 2019. https://doi.org/10.3389/fpsyg.2019.00467

Abstract: While there is a growing literature on “dark traits” (i.e., socially aversive traits), there has been a lack of integration with the burgeoning research literature on positive traits and fulfilling and growth-oriented outcomes in life. To help move the field toward greater integration, we contrasted the nomological network of the Dark Triad (a well-studied cluster of socially aversive traits) with the nomological network of the Light Triad, measured by the 12-item Light Triad Scale (LTS). The LTS is a first draft measure of a loving and beneficent orientation toward others (“everyday saints”) that consists of three facets: Kantianism (treating people as ends unto themselves), Humanism (valuing the dignity and worth of each individual), and Faith in Humanity (believing in the fundamental goodness of humans). Across four demographically diverse samples (N = 1,518), the LTS demonstrated excellent reliability and validity, predicting life satisfaction and a wide range of growth-oriented and self-transcendent outcomes above and beyond existing measures of personality. In contrast, the Dark Triad was negatively associated with life satisfaction and growth-oriented outcomes, and showed stronger linkages to selfish, exploitative, aggressive, and socially aversive outcomes. This exploratory study of the contrasting nomological networks of the Light vs. Dark Triad provides several ways forward for more principled and data driven approaches to explore both the malevolent and beneficent sides of human nature.

Discussion

Across four studies including a wide range of positive and negative outcomes, the Light Triad Scale (LTS) was found to be a reliable and valid measure of a loving and beneficent orientation toward others. While the Light Triad contrasts with the callous and manipulative orientation of the Dark Triad, the Light Triad was not merely the inverse of the Dark Triad. It appears that at least in terms of personality, the absence of darkness does not necessarily indicate the presence of light. As with the literature on positive and negative emotions (Diener and Emmons, 1984; Watson et al., 1988), there appears to be some degree of independence between the Light and Dark Triad, leaving room for people to have a mix of both light and dark traits.

With that said, the Light Triad diverged from the Dark Triad across numerous outcomes drawn from both the Dark Triad and well-being literatures and tended to show stronger outcomes with self-transcendent and growth-fostering outcomes relative to the Dark Triad. Below, we’ll go into greater detail on the contrasting nomological networks of the Light vs. Dark Triad, thereby painting overall portraits of these two very different profiles of human nature.

Portraits of the Light vs. Dark Triad

First, we replicated a number of findings in the Dark Triad literature and extended these findings to the Light Triad. For example, it has been found that Dark Triad traits are correlated with greater childhood unpredictability (Jonason et al., 2013, 2016), aggression (Pailing et al., 2014; Dinic and Wertag, 2018; Knight et al., 2018; Paulhus et al., 2018), utilitarian moral judgment (Djeriouat and Tremoliere, 2014), selfishness, power, money, and sociosexuality (Jonason et al., 2008; Jonason and Buss, 2012; Lee et al., 2013; Kajonius et al., 2015; Jonason and Ferrell, 2016; Balakrishna et al., 2017), and immature defense styles (Richardson and Boag, 2016). We replicated these findings and also found that the Light Triad is significantly correlated with the inverse of these outcomes.

Second, by also investigating a number of growth-fostering and well-being-related outcomes, we could see an overall pattern of findings that paints two very different portraits of humanity. We found that the Dark Triad was positively correlated with being younger, being male, being motivated by power, sex, achievement, and affiliation, having self-enhancement values, immature defense styles, conspicuous consumption, selfishness, and creative work and religious immortality as routes to death transcendence. The Dark Triad was negatively correlated with life satisfaction, conscientiousness, agreeableness, self-transcendent values, compassion, empathy, a quiet ego, a belief that humans are good, and a belief that one’s own self is good.

The Dark Triad was not associated with exclusively adverse and transgressive psychosocial outcomes, however, and some of the correlates of the dark triad may be considered adaptive, at least in limited contexts or “dark niches” (Paulhus, 2014). One example is our replication of the well-known link between the Dark Triad and short-term instrumental sociosexuality (Jonason et al., 2008). Researchers have suggested that the Dark Triad may have evolved precisely because of the reproductive benefits it conferred on our distant ancestors (particularly men) with these Dark Triad characteristics (Jonason et al., 2008). Regardless of the veracity of this evolutionary argument, depending on one’s goals, and the compatibility of those goals with one’s desired sexual partners, high sociosexuality is not necessarily an aversive psychosocial outcome.

The Dark Triad also showed positive correlations with a variety of variables that could facilitate one’s more agentic-related goals. For instance, the Dark Triad was positively correlated with utilitarian moral judgment and the VIA strengths of creativity, bravery, and leadership, as well as assertiveness, in addition to motives for power, achievement, and self-enhancement. Also, an unexpected correlation between the Dark Triad and curiosity was found, which was localized primarily to the embracing and deprivation forms of curiosity.

Interestingly, after controlling for Agreeableness and HEXACO Honesty-Humility, the Dark Triad demonstrated positive associations with various growth-oriented outcomes (e.g., empathy, compassion, quiet ego, and spiritual experience) that were negatively related to the Dark Triad before these antagonistic traits were partialed out. These findings suggest that the callous and manipulative core of the Dark Triad does not do these individuals many favors. It’s likely that the variance that is leftover once the malevolence-related variance of the Dark Triad is removed is associated with agentic extraversion, which may provide a protective factor for those scoring higher on the Dark Triad. This is in line with recent research on narcissism that explicitly separates the antagonistic and agentic extraversion facets of narcissism in predicting well-being (e.g., Kaufman et al., 2018).

In stark contrast, the overall picture provided by the pattern of correlations with the Light Triad was quite different than the Dark Triad. The Light Triad was associated with being older, being female, less childhood unpredictability, as well as higher levels of religiosity, spirituality, life satisfaction, acceptance of others, belief that others are good, belief that one’s self is good, compassion, empathy, openness to experience, conscientiousness, positive enthusiasm, having a quiet ego, and a belief that one can live on through nature and biosociality (having children) after one’s personal death. It is notable that the correlation between the belief that others are good and the Light Triad remained significant even after controlling for Big Five Agreeableness, suggesting that— as initially expected— this belief may be a particularly unique aspect of the Light Triad. Also note that we found a strong correlation between “Humans are Good” and the belief that “I am Good” (r = 0.51, p < 0.001, n = 194). This correlation might be worthy of further investigation in future studies.

Individuals scoring higher on the LTS also reported more satisfaction with their relationships, competence, and autonomy, and they also reported higher levels of secure attachment style and eros in their relationships. In general, the light triad was related to being primarily motivated by intimacy and self-transcendent values. Many character strengths correlated with the Light Triad, including curiosity, perspective, zest, love, kindness, teamwork, forgiveness, and gratitude. Note that the flavor of curiosity associated with Light Triad (primarily stretching) differed from the flavor of curiosity associated with the Dark Triad (primarily embracing and deprivation). Mature defense styles were also associated with the Light Triad, as were optimistic beliefs about the self, the world, and one’s future, as measured by the Beck’s cognitive triad. Individuals scoring higher on the LTS also reported higher self-esteem, authenticity, and a stronger sense of self.

In general, the Light Triad does not appear to be associated with any obvious downsides, with a few possible exceptions depending on the context. The Light Triad was not associated with assertiveness, and was negatively correlated with the motives for achievement and self-enhancement (even though the Light Triad was positively related to productivity and competence). In terms of character strengths, unlike the Dark Triad, the Light Triad was uncorrelated with bravery or assertiveness. Such characteristics may be important for reaching one’s more challenging goals and fully self-actualizing. Additionally, in line with our predictions, the Light Triad was related to greater interpersonal guilt— including survivor, separation, and omnipotence forms of guilt. While it may be adaptive to experience these forms of interpersonal guilt for facilitating relationships and repairing damage in a relationship, these forms of guilt may limit one’s ambitions for fear of succeeding while others remain less successful.

The Light Triad was also correlated with greater “reaction formation,” which consisted of the following items: “If someone mugged me and stole my money, I’d rather he be helped than punished” and “I often find myself being very nice to people who by all rights I should be angry at.” While having such “loving-kindness” even for one’s enemies is conducive to one’s own well-being (see Salzberg, 2017), these attitudes, coupled with greater interpersonal guilt, could make those scoring higher on the Light Triad potentially more open to exploitation and emotional manipulation from those scoring higher on the Dark Triad. Indeed, we believe further investigation of the social interactions between extreme light vs. dark triad scorers would be an interesting future line of research.

Nevertheless, taking all of these patterns together, the Light Triad appears correlated with a greater quality of life overall than the Dark Triad across numerous dimensions of well-being and growth. Again, we’d like to emphasize that no one is all Light or Dark Triad, and we each differ in our balance of these traits. Nevertheless, it should also be noted that the average light-dark balance showed a substantial skew toward the light side of personality, and extreme malevolence was rare in the samples we studied. Indeed, research has shown that, in general, people tend to view the ‘true’ self in others as both good and moral (Strohminger et al., 2017). Anne Frank may have been on to something in her quote at the beginning of this paper.

Limitations

This study was limited in a number of ways. First, in the same tradition of the literature on the Dark Triad, the Light Triad was measured through self-report. While we do not see this as problematic in establishing a new construct, we would like to see more unobtrusive and behavioral measures of both the Light Triad and Dark Triad. For this reason, we included a dictator game that involved the distribution of real money, but more behavioral tasks would provide stronger evidence for the validity of these constructs.

Second, all participants were recruited from paid online survey platforms. While research has shown that the data collected from the platforms we used are generally representative (Buhrmester et al., 2011; Peer et al., 2017), we think a fuller confirmation of the validity of both the Light Triad and Dark Triad would benefit from the investigation of more ecologically valid samples, such as criminals and “saints.” Additionally, further research is required to assess the generalizability of the findings to a wider range of cultures (e.g., non-English speaking countries), as well as races and ethnicities.

Third, construct redundancy is an issue. The same researchers who are not interested in the extra predictive validity of the Dark Triad over and above the inverse Agreeableness and the HEXACO Honesty-Humility facet will likely not be interested in the Light Triad. On the other hand, those conducting more granular research on the Dark Triad may be interested in the differences described in this paper. Additionally, those interested in well-being and positive mental processes more generally may be interested in the Light Triad. This study took the debate about whether the Dark Triad provides additional explanatory power seriously, controlling for these traits in various analyses. We found that many of the stronger first-order correlations with the Light Triad remained significant, though at a much smaller effect size, demonstrating the added predictive validity offered by the Light Triad. Also notably, Honesty-Humility was more strongly correlated with the inverse of the Dark Triad than with the Light Triad, while the Light Triad was more strongly correlated with Agreeableness than with Honesty-Humility, suggesting further divergence between these two constructs.

Future Directions

There are several future directions for research on the Light Triad. Most pressingly, further studies should replicate our findings demonstrating that the Light Triad Scale (LTS) provides useful information over and above the inverse of existing measures of the Dark Triad, Big Five Agreeableness, and the HEXACO Honesty-Humility facet.

Second, as noted above, further research on this topic might benefit from a greater focus on behavioral outcomes, demonstrating that these measures predict differences in behavior between predominantly Light Triad individuals as opposed to predominantly Dark Triad individuals. We believe that the workplace might be a particularly interesting context to explore the effects of Dark Triad and Light Triad individuals on teams, and their relative effects on levels of satisfaction and performance.

Third, research could be done on the occupations and life outcomes associated with the Light vs. Dark triad. Some research has found that individuals with Dark Triad traits are often skilled at climbing organizational hierarchies and negatively impact those around them (Mathieu et al., 2014). What kinds of occupations are most attractive to Light Triad individuals?

Fourth, there is also the question of intervention. Is it possible to enhance Light Triad characteristics? In the current investigation, we found a strong link between the Light Triad and the four main characteristics of a quiet ego: perspective-taking, inclusive identity, detached awareness, and growth-mindedness. Researchers are developing exercises to enhance these characteristics (e.g., Wayment and Bauer, 2017), and it’s an interesting question whether such interventions would also have an effect on Light Triad scores. We also found some evidence that experiences of unity, or self-transcendent experiences (STEs; Yaden et al., 2017a), are positively (though less strongly) correlated with the Light Triad. This raises the possibility that certain kinds of experiences could potentially influence these personality traits. While this is unknown, we believe this would be an exciting area of further study.

Fifth, there is the question of framing. In general, research on this topic ought to be a largely a descriptive endeavor. While we have attempted to be balanced in the foregoing discussion, there is little doubt that we believe that Light Triad individuals are more enjoyable to be around and likely exert a more positive net effect on the world. We acknowledge, however, that it is not our place to moralize these two sub-clinical, interpersonal orientations. Future research should bear this descriptive imperative in mind, and researchers may prefer alternative frameworks to describe the nomological network of these two interpersonal orientations. One alternative framework that is popular within the Dark Triad literature is life history strategy, which employs more neutral labels such as “fast” vs. “slow,” rather than our framing of “adverse” vs. “growth-oriented” (e.g., Jonason et al., 2012b). Therefore, we acknowledge that the overall patterns of results could be interpreted within multiple frameworks in psychology.

Sixth, while the focus of this paper was on the suite of traits that comprise the dark vs. light triad, future research is needed on the differential prediction of the three facets of the LTS: Kantianism, Humanism, and Faith in Humanity. Until such validation and/or further scale development is done, we recommend that researchers focus on the total score of the LTS, as the current studies showed that overall, the LTS is a brief, reliable, and valid measure of an important core of positive traits.

Nevertheless, the current version of the LTS included in these investigations should be viewed as a first-draft, and further studies on a wider range of cultures and over longer stretches of time will have to be conducted to improve the generalizability, reliability, stability, and validity of the Light Triad. Also, while the brevity of the LTS has its advantages, it might not be sufficient to explore the breadth of the Light Triad facets that we discovered. In future work, it might be helpful to go back to a larger pool of items and construct a longer measure.

Finally, just as the scope of dark traits has recently increased beyond the boundaries of the Dark Triad (see Moshagen et al., 2018; Paulhus et al., 2018), the scope of the Light Triad may have to eventually be broadened to include further facets of the positive personality. Since our method of constructing the Light Triad Scale (LTS) was based on a consideration of the conceptual contrast to the Dark Triad, we acknowledge that there could be additional aspects of human beneficence that are not captured by the LTS. Ultimately, a combination of top-down and bottom-approaches will be useful to derive the full breadth of facets that comprise the light personality or the “light character” (Cloninger and Zohar, 2011; Meindl et al., 2015; Garcia and Rosenberg, 2016).

While informing other empirical approaches to studying the moral character, we hope our conceptualization of the Light Triad can also inform a number of philosophical discussions of virtuous character and moral behavior (for a psychology-friendly review of this expansive philosophical literature, see Miller, 2013), as well as more specific philosophical discussions of certain drawbacks to such a temperament, as in Wolf’s (1982) notion of “moral saints” and Schwitzgebel’s (2014) distinction between “jerks” and “sweethearts.” 

Rape myth acceptance is the acceptance of false beliefs, stereotypes, and statements about rape, victims, and perpetrators

Development and validation of the Rape Excusing Attitudes and Language Scale. Rebecka K. Hahnel-Peeters, Aaron T. Goetz. Personality and Individual Differences, Volume 186, Part B, February 2022, 111359. https://doi.org/10.1016/j.paid.2021.111359

Highlights

• RMA scales often contain empirically supported statements.

• We developed and validated an updated RMA scale across two studies (N = 665).

• Our REAL Scale predicted the same amount of variance in the RVES as revised IRMA.

• Our REAL Scale contained no empirically supported items – unlike other RMA scales.

Abstract: Rape myth acceptance (RMA) is the acceptance of false beliefs, stereotypes, and statements about rape, victims, and perpetrators (Burt, 1980). Rape myths become outdated as we learn more about sexual violence. Therefore, psychometric scales should be updated periodically to reflect the more nuanced phenomenon of rape myth acceptance. Several items in the Illinois Rape Myth Acceptance Scale (IRMA; Payne et al., 1999; McMahon & Farmer, 2011) may measure knowledge about the rape perpetrator's psychology rather than rape myth acceptance. In current studies we developed and validated an updated rape myth acceptance scale called the Rape Excusing Attitudes and Language (REAL) Scale without items measuring knowledge about rape. Through exploratory and confirmatory factor analyses on two separate datasets (N = 663), the REAL Scale presents a four factor, 20-item scale. We provide evidence of validation through demonstrating the Scale's convergent and discriminative validity by correlating the REAL Scale with the IRMA and the Rape Victim Empathy Scale (RVES; Smith & Frieze, 2003). We argue that the REAL Scale should be adopted in future studies assessing rape myth acceptance because the items explain the same amount of variance in the RVES as the IRMA, but the REAL Scale displays more face validity.

Keywords: Rape mythsRape myth acceptanceRape Excusing Attitudes and Language ScaleIllinois Rape Myth Acceptance ScaleEvolutionary perspective

2. Some rape myths are not actually myths

By arguing that some statements included in the IRMA Scale are not actually myths, we are not endorsing such statements as morally acceptable. Our sole aim is to update the current scale of measurement to accurately assess rape myths, and we are not seeking to minimize victims' experiences of victim blaming.

Ten of the 22 items on the IRMA Scale can be considered empirically supported statements (see Appendix B for all 10 items and references). By “empirically supported statements,” we are referring to statements on rape myth acceptance scales which may be supported as factually true by existing data within the rape literature. An example of these statements includes: “Girls who are caught cheating on their boyfriends sometimes claim it was rape” (McMahon & Farmer, 2011; Payne et al., 1999).

Data about false rape accusations fall into three themes – including alibis (Kanin, 1994). In a case study of reported rapes recanted by the accusers between 1978 and 1987, 56% (n = 27) provided the complainants with an alibi of sorts. A common reason provided by the women in this category included fear of pregnancy by an affair partner. A replication of Kanin's (1994) study found 32.3% (n = 22) of the 68 reports of forcible rape were classified as false by the complainants' false admissions (Kennedy & Witkowski, 2000). Of these 22 reports, 68% (n = 15) served an alibi function. Other archival analyses of false rape accusations corroborate the alibi motivation of unfounded reports (Kelly et al., 2005; O’Neal et al., 2014).

These findings are important for understanding the motivations that lead to false allegations of rape; however, false accusations of rape are likely to be relatively rare and to occur in specific circumstances. Between 2010 and 2016, an estimated 23% of rapes were reported to the police (Department of Justice et al., 2017). When the “unfounded” or “false” reports of rape are defined through the admission of the complainant, such that the complainant must verbally recant their report, roughly 2 to 10% of reports made to the police are deemed to meet this criterion (Lisak et al., 2010; Weiser, 2017). Therefore, while it is highly unlikely that most victims of sexual assault are lying, it is possible that sometimes women who cheat on their boyfriends falsely report rape as an alibi.

2.1. Items assessing knowledge that rape is sexually motivated

The US Department of Justice defines rape as “the penetration, no matter how slight, of the vagina or anus with any body part or object, or oral penetration by a sex organ of another person, without the consent of the victim” (Sullivan et al., 2017; emphasis added). Rape is a sexual act; therefore, the default assumption should be that the underlying (most likely unconscious) motivation of the perpetrator is one of sexual access.

Anybody can be the target of sexual violence; however, women are most likely to be victims of rape compared to other groups (Buss, 2021). Furthermore, sexual victimization of women seems to center around women's peak fecundity (i.e., the age at which it is easiest for women to become pregnant; Lalumière et al., 2005). Women ages 18 to 25 are at higher risk of victimization of rape compared to all other age groups. Additionally, women are more likely to be targets of victimization when they are sexually available (e.g., unmarried and sexually active). See Lalumière et al. (2005) and Thornhill and Palmer (2000) for a full review of victim and perpetrator demographics.

Furthermore, if rape was solely motivated by a perpetrator's desire to hold power and status over their victims, one might expect women of high status and power to be over-represented in victim statistics (Palmer, 1988; Thornhill & Palmer, 2000). This pattern is not reflected by the current data (Aborisade, 2017; Dinos, 2001; Lutnick, 2019; Silbert & Pines, 1981; Springfield, 2000).

If a woman's vulnerability was more important than sexual desire when choosing a target for sexual assault (Groth, 1979), women who were more vulnerable might be more likely to be a victim of rape – regardless of their attractiveness. This argument predicts that women in age groups that are particularly vulnerable (i.e., very young and very old) are the most likely age groups to be targets of sexual victimization. Data do not support this argument. The most vulnerable age groups, those who are younger and those who are older, are the least likely to be targets of sexual victimization (Lalumière et al., 2005; Thornhill & Palmer, 2000). Finally, if rape was a physically violent act and was motivated by hostile feelings toward women (Groth, 1979), the use of force in rapes might be excessive; however, excessive force is only present in a minority of cases. Most sex offenders use only as much force as needed (Burgess & Holmstrom, 1974; Chappell & Singer, 1977; Friis-Rødel et al., 2021; Hagen, 1979; Katz & Mazur, 1979; Schiff, 1971; Smithyman, 1978).

While a perpetrator's motivation for hostility, dominance, and power could be proximate motivators to rape, it is not a necessary nor sufficient explanation of the phenomenon of rape. Interestingly, it was not until Brownmiller's (1975) book Against Our Will that any explanation excluding sexual access was widely accepted (Palmer, 1988). Importantly, our goal is to prevent as many rapes as possible, and while we agree with other researchers that rape is a repugnant act; we disagree on the underlying motivations. Rape is a sexual act by definition. If one wants to claim that rape is not about sexual access, the onus is on them to show that rape is not about sex. We have detailed arguments against the “not sex” motivation of rape; however, the full extent of these arguments is beyond the scope of this paper (for review see Palmer, 1988; Thornhill & Palmer, 2000; Lalumière et al., 2005).

Working from the assumption that rape is ultimately sexually motivated, several statements on the IRMA Scale may not represent rape myths. For instance: “rape happens when a guy’s sex drive goes out of control;” “if a guy is drunk, he might rape someone unintentionally;” “when guys rape, it is usually because of their desire for sex;” and “guys don’t usually intend to force sex on a girl, but sometimes they get too sexually carried away.” These statements may be measuring understanding of the motivations behind rape rather than false beliefs about rape, victims, and perpetrators. Therefore, the validity of the IRMA Scale may be questioned.

Anticipating academic failure, some students may harm their chances of success (e.g., engaging in destructive behaviors like drug abuse), so that potential failure can be attributed to these handicaps rather than to personal characteristics like low intelligence

Schwinger, M., Trautner, M., Pütz, N., Fabianek, S., Lemmer, G., Lauermann, F., & Wirthwein, L. (2021). Why do students use strategies that hurt their chances of academic success? A meta-analysis of antecedents of academic self-handicapping. Journal of Educational Psychology, Oct 2021. https://doi.org/10.1037/edu0000706

Abstract: Self-handicapping is a maladaptive strategy that students employ to protect their self-image when they fear or anticipate academic failure. Instead of increasing their effort, students may harm their chances of success by procrastinating, strategically withdrawing effort, or engaging in destructive behaviors like drug abuse, so that potential failure can be attributed to these handicaps rather than to stable personal characteristics (e.g., low intelligence). A large body of research has focused on potential antecedents of students’ self-handicapping, but the literature is fragmented and the evidence is often mixed. Thus, we know little about which factors have the highest potential to trigger habitual self-handicapping and to explain interindividual differences in such behaviors. This meta-analysis is the first to synthesize available evidence across a broad range of potential antecedents of academic self-handicapping reported in 159 studies and 194 independent samples (N = 81,630). The strongest associations with habitual self-handicapping were found for the personality traits conscientiousness (r = −.40) and neuroticism (r = .38) as well as stable trait-like factors such as general self-esteem (r = −.34) and fear of failure (r = .39). Rather malleable factors, such as personal achievement goals (rs = −.19 to .27), showed comparatively smaller effects. Self-handicapping assessment (scale and reliability) significantly moderated most of the investigated associations, thereby implying higher internal validities for some measures compared with others. The reported findings provide important insights into mechanisms of and possible starting points for interventions against self-handicapping in the academic domain. 

There was no significant association between religious or spiritual coping, religious service attendance, obesity, and weight

The Association of Religion and Spirituality with Obesity and Weight Change in the USA: A Large-Scale Cohort Study. Nicholas D. Spence, Erica T. Warner, Maryam S. Farvid, Tyler J. VanderWeele, Ying Zhang, Frank B. Hu & Alexandra E. Shields. Journal of Religion and Health, Oct 29 2021. https://link.springer.com/article/10.1007/s10943-021-01368-6

Abstract: The association between religion, spirituality, and body weight is controversial, given the methodological limitations of existing studies. Using the Nurses’ Health Study II cohort, follow-up occurred from 2001 to 2015, with up to 35,547 participants assessed for the religious or spiritual coping and religious service attendance analyses. Cox regression and generalized estimating equations evaluated associations with obesity and weight change, respectively. Religious or spiritual coping and religious service attendance had little evidence of an association with obesity. Compared with not using religious or spiritual coping at all, the fully adjusted hazard ratios (HRs) were minimally different across categories: a little bit (HR = 1.05, 95% CI: 0.92–1.18), a medium amount (HR = 1.09, 95% CI: 0.96–1.24), and a lot (HR = 1.10; 95% CI: 0.96–1.25) (Ptrend = 0.17). Compared with participants who never or almost never attend religious meetings or services, there was little evidence of an association between those attending less than once/month (HR = 1.08, 95% CI: 0.97–1.10), 1–3 times/month (HR = 1.01, 95% CI: 0.90–1.13), once/week (HR = 0.92, 95% CI: 0.83–1.02), and more than once/week (HR = 0.94, 95% CI: 0.82–1.07) (Ptrend = 0.06). Findings were similar for weight change. There was no significant association between religious or spiritual coping, religious service attendance, obesity, and weight change. While religion and spirituality are prominent in American society, they are not important psychosocial factors influencing body weight in this sample.

Decreases in Brain Size and Encephalization in Anatomically Modern Humans: Despite evolutionary pressures on the phenotype, intelligence increased since at least 1870 until recently, due to environmental factors

Decreases in Brain Size and Encephalization in Anatomically Modern Humans. Stibel J.M. Brain Behav Evol, Oct 2021. https://doi.org/10.1159/000519504

Abstract: Growth in human brain size and encephalization is well documented throughout much of prehistory and believed to be responsible for increasing cognitive faculties. Over the past 50,000 years, however, both body size and brain mass have decreased but little is known about the scaling relationship between the two. Here, changes to the human brain are examined using matched body remains to determine encephalization levels across an evolutionary timespan. The results find decreases to encephalization levels in modern humans as compared to earlier Holocene H. sapiens and Late Pleistocene anatomically modern Homo. When controlled for lean body mass, encephalization changes are isometric, suggesting that much of the declines in encephalization are driven by recent increases in obesity. A meta-review of genome-wide association studies finds some evidence for selective pressures acting on human cognitive ability, which may be an evolutionary consequence of the more than 5% loss in brain mass over the past 50,000 years.

Keywords: Brain sizeEncephalizationHuman evolutionHuman cognitionGeneral cognitive functionGeneral cognitive ability

Discussion

The current research supports a growing body of evidence demonstrating a decline in human brain size since at least 50 kyr BP [Henneberg, 1988; Henneberg and Steyn, 1993; Ruff et al., 1997]. As compared to the Upper Paleolithic (approx. 50 kyr BP to 15 kyr BP), brain size has declined by 5.415% (p < 0.001, t test) in modern humans. In addition to declines in absolute brain size, Homo encephalization has also declined significantly during modern periods.

Body size changes appear to explain most of the recent changes to brain size. With the exception of the modern sample, encephalization levels remained relatively stable across the past 50,000 years. While the modern sample demonstrated a relatively low level of encephalization, increases in BMI appear to have driven much of the change. There is strong evidence that encephalization in mammals is best understood in terms of lean body mass [Schoenemann, 2004] and the present results suggest that lean body mass may be a better measure at least with respect to comparing within species over time. The modern sample, adjusted for BMI, showed no significant differences in encephalization as compared to AM Homo. After controlling for obesity, modern brain and body mass appear to scale isometrically relative to the prehistoric AM Homo sample. The results herein suggest that recent reductions in brain size are an adaptive response to changing physiology, particularly as it relates to body mass changes.

Nevertheless, there is strong evidence that brain mass is highly correlated with cognitive function evolutionarily [Bouchard Jr. et al., 1990; Posthuma et al., 2002, 2003; Deaner et al., 2007; Pietschnig et al., 2015; Sniekers et al., 2017; Davies et al., 2018; Nave et al., 2018]. Absent structural changes that have made the brain more efficient and significant decreases in brain mass could lead to reductions in cognitive function irrespective of encephalization. To some extent, it is possible that the overall makeup of the brain could have evolved toward greater functionality within a smaller cavity. The skull appears to have evolved from an elongated to a more globular shape roughly at the same time of the slowdown in cranial capacity growth (between 100 and 35 kyr BP), indicative of structural changes to the brain [Neubauer et al., 2018]. However, fossil evidence supports relatively distributed brain size reductions [Henneberg and Steyn, 1993] or inconsistent variations [Balzeau et al., 2012; Liu et al., 2014]. One study reported significantly smaller frontal lobes in modern humans as compared to some but not all early Homo and Neanderthal specimens [Balzeau et al., 2012], despite this brain region being attributed to higher levels of cognition. In contrast, another study found that modern brains appear to have larger frontal lobes as compared to early Homo [Liu et al., 2014].

While more work is needed, the overall results of the various GWAS studies that have examined evolutionary changes to cognitive ability suggest that both general cognitive function and educational attainment are under negative selection pressure. While the genetic correlations and underlying relationships are still not fully understood, the data support a genetic decrease in cognitive ability consistent with an evolutionary decline in brain size.

There is a paradox to the genetic data, however: despite the selective pressures on cognitive ability noted in the GWAS studies, measures of general intelligence and educational attainment have all risen during much of the past century [Flynn, 1984, 1987, 2009; Barro and Lee, 2013; Pietschnig and Voracek, 2015; Conley and Domingue, 2016; Lee and Lee, 2016]. Intelligence, as with most phenotypes, is determined by genetic and environmental causes. Short-term changes in general intelligence are largely driven by environmental factors – such as health, education, and technology – that can offset or enhance long-term genetic trends [Pietschnig and Voracek, 2015; Bratsberg and Rogeberg, 2018]. Genetic intelligence, in contrast, is driven by heredity. In this way, neither brain size nor genetic intelligence is a predeterminate of general intelligence at an individual, group, or species level.

Aggregated data from 14 countries over nearly a century demonstrate the long-term positive impact of environmental factors on human intelligence [Flynn, 1984, 1987, 2009], a phenomenon known as the Flynn effect. Gains in IQ scores across all countries averaged 0.410 points per year, with the majority of countries showing significant increases (Table 3) between 1932 and 2006. Similar results have been found for educational attainment, with average gains of roughly 0.068 years of growth annually between 1870 and 2010 across more than 100 countries [Barro and Lee, 2013; Lee and Lee, 2016] (Table 4).

Table 3.

General intelligence gains (Flynn effect) across multiple cognitive performance tests for 14 nations from 1932 to 2006

[...]

Table 4.

Educational attainment (EA) gains across over 100 nations from 1870 to 2010

[...]

The incongruity between genetic and environmental effects was highlighted in one of the Health and Retirement GWAS studies [Conley and Domingue, 2016], which directly tested whether the effects of negative selection found in polygenic scores of educational attainment manifested themselves in actual decreases in educational attainment. The authors found, consistent with other studies, that educational attainment is increasing in the population despite evolutionary pressures on the phenotype.

Environmental factors are often more transient than genetics so it is not clear whether physical changes to the brain or genetic predispositions will ultimately produce a negative impact on human cognitive ability. There are, however, signs of a possible reversal in the Flynn effect. A significant decrease in IQ has been noted over the past 30 years in many parts of the globe, with the largest declines occurring across industrialized nations [Shayer et al., 2007; Pietschnig and Voracek, 2015; Bratsberg and Rogeberg, 2018; Flynn and Shayer, 2018]. On an evolutionary timescale, environmental improvements may not be able to offset the long-term impact of genetic and physical changes to the brain. This places into question the ability for natural selection in general to drive species level intelligence beyond an upper bound of fitness.

Statements that sounded superficially impressive but lacked intent to communicate meaning generated meaning-seeking, but only when delivered by high admirability speakers (the Dalai Lama) as compared to low admirability speakers (Kim Kardashian)

Kara-Yakoubian, Mane, Ethan A. Meyers, Constantine Sharpinskyi, Anna Dorfman, and Igor Grossmann. 2021. “Hidden Wisdom or Pseudo-profound Bullshit? the Effect of Speaker Admirability.” PsyArXiv. October 28. doi:10.31234/osf.io/tpnkw

Abstract: How do people reason in response to ambiguous messages shared by admirable individuals? Using behavioral markers and self-report questionnaires, in two experiments (N = 571) we examined the influence of speakers’ admirability on meaning-seeking and wise reasoning in response to pseudo-profound bullshit. In both studies, statements that sounded superficially impressive but lacked intent to communicate meaning generated meaning-seeking, but only when delivered by high admirability speakers (e.g., the Dalai Lama) as compared to low admirability speakers (e.g., Kim Kardashian). The effect of speakers’ admirability on meaning-seeking was unique to pseudo-profound bullshit statements and was absent for mundane (Study 1) and motivational (Study 2) statements. In Study 2, participants also engaged in wiser reasoning for pseudo-profound bullshit (vs. motivational) statements and did more so when speakers were high in admirability. These effects occurred independently of the amount of time spent on statements or the complexity of participants’ reflections. It appears that pseudo-profound bullshit can promote epistemic reflection and certain aspects of wisdom, when associated with an admirable speaker.

Check also “Who said it?” How contextual information influences perceived profundity of meaningful quotes and pseudo‐profound bullshit. Vukaڑin Gligoriو  Ana Vilotijeviو. Applied Cognitive Psychology, December 20 2019. https://doi.org/10.1002/acp.3626

Rethinking the Diagnosis of Mental Disorders: Data-Driven Psychological Dimensions, Not Categories, as a Framework for Mental-Health Research, Treatment, and Training

Rethinking the Diagnosis of Mental Disorders: Data-Driven Psychological Dimensions, Not Categories, as a Framework for Mental-Health Research, Treatment, and Training. Christopher C. Conway, Robert F. Krueger, HiTOP Consortium Executive Board. Current Directions in Psychological Science, April 27, 2021. https://doi.org/10.1177/0963721421990353

Abstract: Generations of psychologists have been taught that mental disorder can be carved into discrete categories, each qualitatively different from the others and from normality. This model is now outdated. A preponderance of evidence indicates that (a) individual differences in mental health (health vs. illness) are a matter of degree, not kind, and (b) broad mental-health conditions (e.g., internalizing) account for the tendency of narrower ones (e.g., depression, social anxiety, panic) to co-occur. With these observations in mind, we discuss an alternative diagnostic system, called the Hierarchical Taxonomy of Psychopathology (HiTOP), that describes the broad and specific components of mental disorder. It deconstructs traditional diagnostic categories, such as those listed in the Diagnostic and Statistical Manual of Mental Disorders, and recasts them in terms of profiles of dimensions. Recent findings support the utility of this approach for mental-health research and intervention efforts. HiTOP has the potential to put mental-health research, training, and treatment on a much sounder scientific footing.

Keywords: classification, diagnosis, Hierarchical Taxonomy of Psychopathology (HiTOP), individual differences, mental disorder

Gay men preferred more masculinized faces than did bisexual men; tops preferred feminized faces, whereas bottoms & versatiles preferred masculinized faces; South China gay men preferred more masculinized faces than did those living in North China

Demographic and Geographic Differences in Facial Masculinity Preferences Among Gay and Bisexual Men in China. Lijun Zheng & Jing Zhang. Archives of Sexual Behavior, Oct 25 2021. https://link.springer.com/article/10.1007/s10508-021-02082-w

Abstract: This study examined demographic and geographic differences in facial masculinity preferences among gay and bisexual men in China. The final sample included 2595 participants whose data were obtained from four published data sets and one unpublished data set. Demographic variables included sexual self-label, sexual orientation, age, educational level, and occupational status. Geographic variables were classified based on the IP addresses of respondents including North–South division, administrative division, economic regional division, and modernization division. There were significant differences in facial masculinity preferences in demographic variables. Gay men preferred more masculinized faces than did bisexual men. “Tops” preferred feminized faces, whereas “bottoms” and “versatiles” preferred masculinized faces. Participants aged 20–29 years preferred more masculinized faces than did those aged 16–19 years and older than 30. Also, the results indicated significant differences in facial masculinity preferences in geographic variables. Participants living in South China preferred more masculinized faces than did those living in North China. Concerning administrative division, individuals living in South China (Guangdong, Guangxi, Fujian, and Jiangxi) preferred more masculinized faces than did those living in other regions. Participants living in first-tier cities (Beijing, Shanghai, Guangzhou, and Shenzhen) preferred more masculinized faces than did those living in other cities. The findings implicated context-dependent variability in facial masculinity preferences among gay and bisexual men; facial trait-attribution processes may contribute to these individual differences.

Rolf Degen summarizing... Large-scale, long-term study that allows tracking of individual developments gives the all-clear as regards the dangers of intensive social media use for adolescents

The complex association between social media use intensity and adolescent wellbeing: A longitudinal investigation of five factors that May affect the association. Maartje Boer et al. Computers in Human Behavior, October 28 2021, 107084. https://doi.org/10.1016/j.chb.2021.107084

Highlights

• On average, within-person changes in SMU intensity and wellbeing were not related.

• Within-person relations between SMU and wellbeing varied across adolescents.

• At the between-person level, more SMU was somewhat related to less wellbeing.

• Between-person relations between SMU and wellbeing were confounded by SMU problems.

• Active and passive SMU did not yield differential associations with wellbeing.

Abstract: The present study examined five possible explanations for the mixed findings on the association between adolescents' social media use (SMU) intensity and wellbeing. Particularly, it investigated whether the association between SMU intensity and life satisfaction depended on (1) the type of SMU activity the adolescent engaged in, (2) the (non)linearity of the association, (3) individual differences, (4) inclusion of SMU problems, and (5) the level of analysis. Data from four waves of longitudinal data among 1419 adolescents were used (Mage(T1) = 12.51 (0.60), 45.95% girl). Multilevel analyses showed that at the within-person level, on average, changes in different types of SMU activities were not associated with changes in life satisfaction. Within individuals, the associations ranged from negative to positive across adolescents. In general, this variation could not be explained by adolescents' engagement in upward social comparisons. At the between-person level, the higher adolescents' average intensity of certain SMU activities, the lower their average level of life satisfaction. However, these associations were confounded by adolescents’ SMU problems. No curvilinear associations were found. Overall, the findings underline that to enhance our understanding of the association between SMU and wellbeing in adolescence, it is important to acknowledge the heterogeneity of effects, distinguish between SMU intensity and SMU problems, and disentangle within-from between-person effects.

Keywords: Social media useWellbeingLife satisfactionAdolescentsLongitudinal study

4. Discussion

The present study investigated the extent to which the association between SMU intensity and wellbeing is dependent on (1) the SMU activity adolescents engage in, (2) the (non)linearity of the association, (3) individual differences, (4) whether SMU problems are considered, and (5) the level of analyses. In doing so, we distinguished SMU activities ranging from more active (i.e., SNS posting, IM sending, SNS responding, SNS liking) to more passive (i.e., SNS viewing, IM viewing). Wellbeing was indicated by life satisfaction. At the within-person level, there was no average association between any of the SMU activities and life satisfaction, regardless of whether we controlled for SMU problems. However, the associations at the within-person level varied: For some adolescents, increases in SMU activities were associated with decreases in life satisfaction, whereas for others, increases in SMU activities were associated with increases in life satisfaction. In general, this variation could not be explained by adolescents' tendency to engage in upward social comparisons. At the between-person level, higher average intensity of some more passive activities (i.e., SNS and IM viewing) and one more active (i.e., IM sending) activity were associated with lower average life satisfaction with a small effect size. However, these associations disappeared when controlling for adolescents’ average level of SMU problems. In addition, for none of the SMU activities, evidence was found that the association between SMU intensity and life satisfaction was curvilinear.

Our findings highlight the importance of three factors for understanding the association between SMU activities and wellbeing in adolescence. First, answering the question whether the association between SMU intensity and wellbeing differs across adolescents (RQ3a), our findings showed that within-person effects of SMU intensity ranged from positive to negative across adolescents. This result is in line with experience sampling studies showing that for some adolescents, momentary increases in the intensity of SMU activities were associated with momentary decreases in wellbeing, but for others with increases or no changes in wellbeing (Beyens, Pouwels, Valkenburg, & Van Driel, 2020; Beyens, Pouwels, Van Driel et al., 2020). This study extends these findings as it revealed that also with annual assessments, associations between adolescents’ intensity of SMU activities and life satisfaction varied across adolescents.

Second, answering the question whether a negative association between SMU intensity and wellbeing is driven by SMU problems (RQ4), our findings indicated that negative between-person associations between certain SMU activities and life satisfaction disappeared when controlling for SMU problems. These findings suggest that a negative association between SMU intensity and life satisfaction may be explained by the presence of SMU problems rather than by engagement in specific SMU activities. Therefore, negative associations between SMU intensity and wellbeing revealed in previous studies may have been driven by unobserved SMU problems (e.g., Kelly et al., 2018; Twenge et al., 2018). However, even after controlling for SMU problems, we found that the within-person associations between the SMU activities and life satisfaction ranged from negative to positive. Hence, for some adolescents, increases in SMU activities were associated with decreases in life satisfaction, which could not be attributed to increases in SMU problems.

Third, related to our question at which level a negative association between SMU intensity and wellbeing occurs (RQ5), we found no average associations at the within-person level, while there were negative associations at the between-person level (although only when not controlling for SMU problems). This finding demonstrates that between-level associations do not necessarily reflect within-person dynamics, which was also found in earlier longitudinal studies (Beeres et al., 2020; Coyne et al., 2020; Orben et al., 2019). Conceptually, this finding suggests that the observed between-person association between higher SMU intensity and lower wellbeing was not a causal relation, as changes in SMU intensity were not related to changes in wellbeing within an adolescent.

Above all, some of the factors affecting the association between SMU intensity and life satisfaction need to be considered in concert when understanding this association. As noted above, SMU problems confound the association between certain SMU activities and life satisfaction, but only with regards to between-person associations.

We also examined which type of SMU activity could be detrimental to wellbeing (RQ1). At the within-person level, we found no average associations between any of the SMU activities and life satisfaction, which aligns with findings from experience sampling studies (Beyens, Pouwels, Van Driel et al., 2020; Jensen et al., 2019). At the between-person level, the observed negative associations between adolescents' intensity of engaging in SMU activities and life satisfaction were not specific to passive SMU activities, as proposed by researchers (Liu et al., 2019; Verduyn et al., 2017). In line with our findings, other studies also showed that adolescents’ active as well as passive SMU activities were negatively correlated with their wellbeing at the between-person level (Beyens, Pouwels, Van Driel et al., 2020). Passive and active SMU activities are possibly difficult to disentangle, because adolescents often engage in such SMU activities simultaneously (Valkenburg, Van Driel, & Beyens, 2021). For example, responding to a message on an IM requires viewing that message first. Accordingly, our study showed very high correlations between IM sending and IM viewing at the between-person level. As such, their differential associations with wellbeing may be difficult to grasp, which may explain why in our study IM sending and IM viewing were both negatively related to life satisfaction. However, we stress that these negative associations disappeared when we controlled for SMU problems.

Based on the Goldilocks hypothesis (Przybylski & Weinstein, 2017), we also investigated whether the association between SMU intensity and wellbeing was nonlinear (RQ2), which was not confirmed in our study. Findings of the present study are thereby consistent with other longitudinal studies that did not find curvilinear associations (Houghton et al., 2018; Jensen et al., 2019). Curvilinear associations were mainly found in cross-sectional studies (Przybylski & Weinstein, 2017; Twenge et al., 2018), which could imply that the Goldilocks hypothesis applies to associations at the between-person level at one particular timepoint. Alternatively, earlier found curvilinear associations may have been country-specific. International research shows that the association between adolescents’ SMU and wellbeing are susceptible to country-level factors, for example the extent to which social media are adopted among youth within society (Boer et al., 2020).

Further, we examined whether the association between adolescents’ SMU intensity and wellbeing would depend on the tendency to engage in upward social comparisons (RQ3b). We found no evidence for this moderating effect, with one exception: Among adolescents reporting high levels of upward social comparison, increases in SNS liking were associated with decreases in life satisfaction, which supports the social comparison perspective (De Vries et al., 2018). Among adolescents reporting low levels of upward social comparison, increases in SNS liking were associated with increases in life satisfaction, which corresponds to the emotional contagion perspective (De Vries et al., 2018). However, the individual differences in the associations between SNS liking and life satisfaction were not reduced when upward social comparisons were considered. Also, this was the only moderating effect found out of the six SMU activities that were examined. Therefore, future studies are necessary to replicate our findings.

Our findings provide several implications for future research on the association between SMU intensity and adolescent wellbeing. Specifically, future longitudinal studies that acknowledge heterogeneity in effects, consider SMU problems, and distinguish between within-person and between-person effects would be promising. Research considering these three factors seems more informative than research aiming to disentangle the effects of different SMU activities or examining curvilinear associations. Furthermore, our findings illuminate why earlier studies on the link between SMU intensity and adolescent wellbeing are so inconsistent: Depending on whether researchers investigate specific groups of adolescents, control for SMU problems when examining SMU intensity, or study within-person or between-person associations, the link can range from positive to negative.

In addition, our findings can also inform those concerned with the wellbeing of adolescents, including parents and teachers. They suggest that most adolescents engaging in higher SMU intensity are not at risk for impairments in wellbeing, regardless of whether this concerns engaging in more active or more passive SMU activities. Higher SMU intensity may be considered as normative adolescent behavior that contributes to adolescents’ individual development and daily interaction with peers (Granic, Morita, & Scholten, 2020; Valkenburg & Peter, 2011). Nevertheless, our findings imply that risks to wellbeing could arise when adolescents report SMU problems, indicated by symptoms of addiction (e.g., loss of control over SMU). Therefore, investing in the prevention, early detection, and treatment of problematic SMU may be warranted. Yet, our findings also showed that for a particular group of adolescents, increases in SMU intensity are indicative of decreased wellbeing. Research focusing on identifying the individual characteristics that make adolescents vulnerable to negative SMU effects could provide directions for targeted prevention or intervention programs.

Although we tested many ways in which adolescents’ SMU and their wellbeing could be related, the association may be dependent on more factors that were not addressed in this study. First, it may depend on whom adolescents have contact with on social media. For example, longitudinal research on adults showed that receiving Facebook messages from close friends increased wellbeing, whereas receiving such messages from acquaintances did not change wellbeing (Burke & Kraut, 2016). Other research showed that adolescents who reported more Instagram use with close friends reported more friendship closeness than adolescents who showed less Instagram use with close friends (Pouwels, Valkenburg, Beyens, Van Driel, & Keijsers, 2021). This association was not observed with regards to Instagram use without close friends (Pouwels et al., 2021). Second, the association may depend on the wellbeing outcome being studied. Meta-analytic findings indicate that SMU intensity has different associations with self-esteem and social capital than with life satisfaction (Meier & Reinecke, 2020). Furthermore, research suggests that the association is different for positive indicators of wellbeing than for negative indicators, for example depression and negative affect (Huang, 2017; Wirtz, Tucker, Briggs, & Schoemann, 2020). Third, the association may be contingent on the social media platform used. More specifically, the use of highly visual social media, such as Instagram and Snapchat, may induce more impact than less visual social media, such as Facebook and Twitter. Highly visual social media are mainly focused on uploading visual content, including photos and videos, and allow users to edit this content in more appealing ways using filters (McCrory, Best, & Maddock, 2020). Exposure to modified idealized online portrayals may reinforce a negative body image, which, in turn, could undermine wellbeing (Marengo, Longobardi, Fabris, & Settanni, 2018).

4.1. Strengths and limitations

Using four waves of longitudinal data among secondary school adolescents and a systematic multilevel analytical approach, the present study examined five factors that possibly affect the association between SMU intensity and wellbeing. However, results of this study should be interpreted while considering several limitations. The yearly time intervals of the data used in the present study only allowed for estimating long-term associations. Consequently, potential short-term effects of the intensity of SMU activities could not be captured. Yet, findings from studies on the association between different SMU activities and wellbeing using (multiple) daily assessments showed some comparable results. Often, these studies also observed no average within-person relation between passive and active SMU activities and wellbeing. Also, they showed that these within-person associations ranged from negative to positive across adolescents (Beyens, Pouwels, Valkenburg, & Van Driel, 2020; Beyens, Pouwels, Van Driel et al., 2020; Jensen et al., 2019). Additionally, self-report measures of adolescents’ SMU intensity may not accurately represent actual use, because adolescents may over- or underestimate their use. Indeed, research showed a moderate correlation between self-report and tracked SMU (Parry et al., 2020). Research replicating our study using tracked data of SMU activities is warranted. In addition, the present analyses did not explore the direction of the associations between the intensity of SMU activities and life satisfaction. Studying directionality would require a different analytical approach (e.g., random intercept cross-lagged panel modelling), which cannot be adopted within the present multilevel framework. Although we examined life satisfaction as an outcome of higher SMU intensity, a reverse order may be plausible as well. A meta-analysis on the direction of the association supports our assumption, although it investigated the direction of the relation between screen time in general and depression symptoms (Tang, Werner-Seidler, Torok, Mackinnon, & Christensen, 2021). Finally, the data included considerable dropout of adolescents, which may have affected the quality of the data, especially in the final wave. However, this dropout was mostly not due to individual refusal (i.e., not due to selective dropout), but to classes and schools dropping out. Also, we aimed to limit any potential bias by imputing missing data based on available data at all waves (Madley-Dowd et al., 2019).