Friday, October 11, 2019

Age is the most important risk factor for loneliness, which peaks just prior to the peak age of onset for psychotic disorders; contrary to expectations, it declines thereafter over the lifespan

Shovestul, Bridget, Jiayin Han, Laura Germine, and David Dodell-Feder. 2019. “Risk Factors for Loneliness: The High Relative Importance of Age Versus Other Factors.” PsyArXiv. October 11. doi:10.31234/

Background: Loneliness is a potent predictor of negative health outcomes making it important to identify risk factors for loneliness. Though extant studies have identified characteristics that are associated with loneliness, less is known about the cumulative and relative importance of these factors, and how their interaction may impact loneliness. Thus, here, we investigate risk factors for loneliness.
Methods: 4,885 individuals ages 10-97 years from the US completed the three-item UCLA Loneliness Survey on Using census data, we calculated the population and community household income of participants’ census area, and the proportion of individuals in the participant’s census area that shared the participant’s demographic characteristics (i.e., sociodemographic density). We evaluated the relative importance of three classes of variables for loneliness risk: those related to the person (e.g., age), place (e.g., community household income), and the interaction of person X place (sociodemographic density).
Results: We find that loneliness is highly prevalent and best explained by person (age) and place (community household income) characteristics. Of the variance in loneliness accounted for, the overwhelming majority was explained by age. On age, loneliness peaks at 19 years, and declines thereafter. The congruence between one’s sociodemographic characteristics and that of one’s neighborhood had no impact on loneliness.
Conclusions: Age appears to be the most important risk factor for loneliness, which peaks just prior to the peak age of onset for psychotic disorders, and, contrary to popular belief, declines thereafter over the lifespan. These data may have important implications for public health interventions.

Youth marijuana use can have adverse health outcomes; however, reports from Colorado, Oregon, & Washington indicate no statewide increase in youth marijuana use following retail legalization for adults

Ta M, Greto L, Bolt K. Trends and Characteristics in Marijuana Use Among Public School Students — King County, Washington, 2004–2016. MMWR Morb Mortal Wkly Rep 2019;68:845–850.


What is already known about this topic?
Youth marijuana use can have adverse health outcomes. However, reports from Colorado, Oregon, and Washington indicate no statewide increase in youth marijuana use following retail legalization for adults.

What is added by this report?
Following 2012 legalization of retail marijuana sale to adults in Washington, past 30–day marijuana use decreased or remained stable through 2016 among King County students in grades 6, 8, 10, and 12. Among grade 10 students, the decline in use occurred among males while the rate among females remained steady. Use of alcohol or other substances was four times as frequent among marijuana users as among nonusers.

What are the implications for public health practice?
Understanding reasons for youth marijuana use, particularly among females, might help inform policy, strategies, and educational campaigns.

Use of marijuana at an early age can affect memory, school performance, attention, and learning; conclusions have been mixed regarding its impact on mental health conditions, including psychosis, depression, and anxiety (1–3). Medical marijuana has been legal in Washington since 1998, and in 2012, voters approved the retail sale of marijuana for recreational use to persons aged ≥21 years. The first retail stores opened for business in July 2014. As more states legalize marijuana use by adults aged ≥21 years, the effect of legalization on use by youths will be important to monitor. To guide planning of activities aimed at reducing marijuana use by youths and to inform ongoing policy development, Public Health—Seattle & King County assessed trends and characteristics of past 30–day marijuana use among King County, Washington, public school students in grades 6, 8, 10, and 12. This report used biennial data for 2004–2016 from the Washington State Healthy Youth Survey. Among grade 6 students there was a decreasing trend in self-reported past 30–day marijuana use from 2004 to 2016, while the percentage of grade 8 students who had used marijuana during the past 30 days did not change during that period. Among students in grades 10 and 12, self-reported past 30–day use of marijuana increased from 2004 to 2012, then declined from 2012 to 2016. In 2016, the percentage of students with past 30–day marijuana use in King County was 0.6% among grade 6, 4.1% among grade 8, 13.9% among grade 10, and 25.5% among grade 12 students. Among grade 10 students, 24.0% of past 30–day marijuana users also smoked cigarettes, compared with 1.3% of nonusers. From 2004 to 2016 the prevalence of perception of great risk of harm from regular marijuana use decreased across all grades. Continued surveillance using consistent measures is needed to monitor the impact of marijuana legalization and emerging public health issues, given variable legislation approaches among jurisdictions.

The Healthy Youth Survey is a school-based, anonymous, self-administered, cross-sectional survey conducted in the fall of even-numbered years in Washington public schools.* Schools with grades 6, 8, 10, and 12 are randomly selected using a clustered sampling design. Schools not selected for the state sample also can choose to participate in the survey. The survey measures risk behaviors, attitudes, and factors that contribute to youth health and safety, including alcohol, marijuana, tobacco, and other drug use; behaviors that result in unintentional and intentional injuries (e.g., violence); dietary behaviors, and physical activity.

This analysis used data from all participating schools, both sampled and nonsampled, representing all 19 King County school districts for biennial survey years 2004 through 2016 (the most currently available year of data at the time of analysis). King County is the largest metropolitan county in the state. Local jurisdictions have authority to regulate land uses and can impose additional time, place, and manner-of-use restrictions on state licensed businesses; thus, considerable variation in the availability of and restrictions on retail marijuana exists across the 39 cities in King County, including Seattle.

Survey response rates varied by grade and survey year, with higher rates in more recent surveys.† During 2004–2016, King County response rates ranged from 60%–80% for grades 6 and 8; 50%–70% for grade 10; and 40%–50% for grade 12. For the 2016 survey, response rates for King County were 80% for grades 6 and 8, 70% for grade 10, 40% for grade 12, and 67% for all grades combined.

Data representing substance use, perception of great risk of harm, risky behaviors, and factors associated with marijuana use were categorized dichotomously. Past 30–day marijuana use was considered use on 1 or more days during the past 30 days. Perceived great risk of harm associated with regular marijuana use (more than one or two times per week) was categorized dichotomously as great risk versus all other options combined (moderate, slight, and no perceived risk). Past 30–day use of alcohol, cigarettes, and electronic cigarettes/vape pens was considered use on 1 or more days in the past 30 days, past 30–day risky driving and riding behaviors,§ were considered one or more occurrences during the past 30 days and past binge drinking¶ was over a 2-week period.

Dichotomous factors generally reported to be associated with other substance use (4) were examined for marijuana use; these factors included whether students’ parents had talked about not using marijuana, use by one or more best friends or by a member in the youth’s household, and having been bullied one or more times in the past month.** Stata survey software (version 13; StataCorp) was used to generate percentage estimates and corresponding 95% confidence intervals (CIs). To account for differential participation among school districts across survey years, percentage estimates were weighted to the school district total enrollment by grade and sex, with the final weights adjusted to sum to the county total public school enrollment by grade and sex. Joinpoint trend analysis software ( icon) was used to evaluate statistical significance of trends in survey-weighted percentage estimates by grade and sex. Analyses of trends by sex and examination of factors associated with past 30–day use were restricted to grade 10 students as a result of grade-specific sampling and the need for adequate response rates to accommodate a robust analysis.

During 2004–2016, the prevalence of reported past 30–day marijuana use was lowest among students in grade 6 and increased with school grade level (Figure 1). In 2016, past 30–day marijuana use was reported by 0.6% (CI = 0.4–0.7) of grade 6 students, 4.1% (CI = 3.5–4.8) of grade 8 students, 13.9% (CI = 12.6–15.3) of grade 10 students, and 25.5% (CI = 23.7–27.4) of grade 12 students in King County. Among students in grade 6, past 30–day marijuana use declined significantly, from 1.3% in 2004 to 0.6% in 2016. There was no statistically significant trend among students in grade 8; however, among students in grades 10 and 12, past 30–day use increased from 2004 to 2012, and then declined. Across all grades, the percentage of students reporting great risk of harm from regular marijuana use declined over the survey period, with the lowest perceived great risk of harm reported among older students in all years. In 2016, 26.7% (CI = 25.0–28.5) of students in grade 12 perceived great risk of harm from regular marijuana use, whereas 53.3% (CI = 50.5–56.1) reported this perception in 2004.

Among male students in grade 10, past 30–day marijuana use increased from 17.6% in 2004 to 21.4% in 2010 and subsequently declined to 13.5% in 2016 (Figure 2). Among female students in grade 10, there was no change in the prevalence of past 30–day use, which remained approximately 16% during this period. In 2016, there was no significant difference in past 30–day marijuana use between male and female students in grade 10.

Among past 30–day marijuana users in grade 10, 42.8% reported living with someone who uses marijuana, 88.5% reported having at least one best friend who used marijuana, and 26.3% reported having been bullied at least once in the past 30 days; these prevalences were higher than those among grade 10 nonusers (12.8%, 28.3%, and 16.5%, respectively) (Table). Among grade 10 marijuana users, 92.5% reported that it was not very hard to obtain marijuana, compared with 56.7% of nonusers. No parental discussion about marijuana during the past year was reported by similar percentages of past 30–day marijuana users (39.2%) and nonusers (39.8%).

Among grade 10 students, prevalence of past 30–day use of other substances was four times higher among those who had used marijuana in the past 30 days than among those who had not. Among marijuana users, the prevalences of past 30–day use of other substances were as follows; alcohol (67.0%), cigarettes (24.0%), e-cigarettes or vape pens (43.0%), and of binge drinking (43.5%), compared with 10.3%, 1.3%, 4.0%, and 3.7% among nonusers, respectively. Among grade 10 marijuana users, 36% reported driving within 3 hours of using marijuana at least once in the past month.


Despite legalization of the retail sale of marijuana to adults in Washington in 2012, evidence from the biennial Washington State Healthy Youth Survey indicates that the prevalence of past 30–day marijuana use among students in grades 10 and 12 began to decline that year. The decline continued in 2016 among grade 10 students and did not change significantly among grade 12 students. This decline or absence of change in youth marijuana use after legalization of retail sales to adults is consistent with trends reported in Colorado and Oregon,†† states that legalized adult retail sales of marijuana in 2013 and 2014, respectively. However, causality of the observed decrease in youth use following retail sale legalization cannot be inferred, because effects might be delayed and this report does not include data from the timeframe that would capture the more recent surge in e-cigarette use by youth and the use of tetrahydrocannabinol (THC) within electronic cigarette (e-cigarette) devices. Although the relationship between legal adult recreational use and youth use is not well understood, two possible reasons for the observed decline in youth use include reduction of illicit market supply through competition§§ and loss of novelty appeal among youths. Furthermore, it would be important to monitor the long-term role legalization might play to foster a permissive use environment given observed strong associations with use and individual and family factors that influence youth use.

Before initiation of retail marijuana sales in Washington in 2014, the statewide prevalence of use among grade 10 students had not changed significantly since 2002, although reported statewide use prevalence in 2016 was higher among students identifying as non-Hispanic American Indian/Alaska Native and Hispanic than among non-Hispanic white and non-Hispanic Asian students (5). Among grade 10 King County students, past 30–day marijuana use by male students has been decreasing since 2010, while the prevalence among female students has not changed. Continued monitoring is necessary to observe how local trends among males change over time. The narrowing of the sex difference gap reflects national trends (6) and suggests that female users might benefit from tailored prevention messages informed by an understanding of reasons for use.

Although overall youth rates of smoking and alcohol are declining nationally (7), the prevalence of any substance use, including alcohol, cigarettes, or vape pens, was four times higher among grade 10 past 30–day marijuana users than among nonusers. Statewide data from 2016 also show similar higher prevalence of household, peer and individual factors associated with youth substance use among grade 10 marijuana users than nonusers ( iconexternal icon). Findings from a 2017 survey of Canadian residents aged 15–24 years found that marijuana users were significantly more likely to be past 30-day e-cigarette users, compared with nonusers (8). Polysubstance use and driving after using marijuana or riding in a car driven by someone who had used marijuana recently are public health issues that are important to monitor. Educational campaigns conveying health risk of marijuana use should also address impaired driving, in light of experimental data showing deteriorating control with increasing task complexity and increased risk for involvement in a motor vehicle crash (9).

The findings in this report are subject to at least six limitations. First, these data predate the recent reported increase in youth e-cigarette use and the use of THC in the newest generation of e-cigarette devices. The marijuana use question does not explicitly define use by method and estimates of youth marijuana use might be underestimated if respondents did not consider vaping or edible consumption of marijuana products when responding to the question. Second, data are from public school students only and might not be generalizable to all youths in this age group. Students who might be at higher risk might not be in school; it is estimated that 95.3% of King County residents aged 14–18 years are in school.¶¶ Third, survey participation is voluntary, and responses are based on self-report, which can be subject to recall or response bias. Fourth, these estimates might differ from other state or nationally representative youth health–surveillance systems, in part because of survey methods, age of participants, survey setting, and period during the year the survey was conducted. Fifth, local historical data for youth marijuana use before 2004 are not available, and the effects of medical marijuana legalization, which occurred in 1998, on use by youths is unknown. Finally, binge drinking is framed as five or more drinks in a row during the preceding 2 weeks for both males and females and would likely underestimate excessive alcohol consumption among females compared with using a sex-specific four-drink threshold (10).

The national goals for substance use set by Healthy People 2020*** include a target of 6% for youths aged 12–17 years with past 30–day marijuana use, and progress toward this target requires evidence-based interventions and policies for preventing and treating substance use and abuse among youths. Although some cross-cutting interventions addressing adolescent health are presented in the Community Preventive Task Force’s Community Guide,††† there currently is no specific category for marijuana use, as there is for alcohol and tobacco. The National Registry of Evidence-based Programs and Practices,§§§ a project of the federal Substance Abuse and Mental Health Services Administration, might be a potential alternative source for strategies that reduce marijuana use and prevent associated harms, but these strategies might not be sufficient for states with newly legalized retail marketplaces. In light of the limited evidence base, there is a need to identify individual, relationship, community, and societal determinants of youth substance use that would allow development of broad-based risk-reduction strategies. Continued surveillance would benefit from having a set of standard measures across jurisdictions to monitor the health impacts of retail marijuana sale legalization among states.

Language has emerged in no other species than humans, suggesting a profound obstacle to its evolution; maybe quite specific social conditions were prerequisite for the evolution of language- and symbol-ready hominins

The Role of Egalitarianism and Gender Ritual in the Evolution of Symbolic Cognition. Camilla Power. August 2019. Chp 19 in Handbook of Cognitive Archaeology, Routledge.

Abstract: Are there constraints on the social conditions that could have given rise to language and symbolic cognition? Language has emerged in no other species than humans, suggesting a profound obstacle to its evolution. If language is seen as an aspect of cognition, limitations can be expected in terms of computational capacity. But if it is seen it as fundamentally for communication, then the problems will be found in terms of social relationships. Below a certain threshold of cooperation and trust, no language or symbolic communication could evolve (Knight & Lewis, 2017a); this has been termed a “platform of trust” (Wacewicz, 2017).... In this chapter, I argue that quite specific social conditions were prerequisite for the evolution of language- and symbol-ready hominins. One of the requirements differentiating our ancestors from other African apes was a switch to mainly female philopatry – females living with their relatives, rather than dispersing at sexual maturity – coevolving with an increasing tendency to egalitarianism....How did increasing egalitarianism affect males and potentially “feminize” male behavior for cooperative offspring care? How were male and female relations affected in the evolution of genus Homo and Homo sapiens?

We are capable of making accurate personality judgements in computer-mediated communication by means of even small cues like nicknames

The Name Is the Game: Nicknames as Predictors of Personality and Mating Strategy in Online Dating. Benjamin P. Lange et al. Front. Commun., February 12 2019.

Objective: We investigated the communicative function of online dating nicknames. Our aim was to assess if it is possible to correctly guess personality traits of a user simply by reading his/her nickname.

Method: We had 69 nickname users (average age: 33.59 years, 36 female) complete questionnaires assessing their personality (Big 5 + narcissism) and mating strategy (short- vs. long-term). We then checked (using a total of 638 participants, average age: 26.83 years, 355 female), whether personality and mating strategy of the nickname users could be assessed correctly based only on the nickname. We also captured the motivation to contact the user behind a nickname and looked at linguistic features of the nicknames.

Results: We found that personality and mating strategy could be inferred from a nickname. Furthermore, going by trends, women were better at intersexual personality judgments, whereas men were better in intrasexual judgements. We also found several correlates of the motivation to contact the person behind the nickname. Among other factors, long nicknames seemed to deter people from contacting the nickname user.

Conclusions: Findings display that humans are capable of making accurate personality judgements in computer-mediated communication by means of even small cues like nicknames.


Language-based face-to-face (ftf) interaction can be considered the most natural way of communication (Kock, 2004). New social media have transformed communication, though, as sender and receiver are not necessarily copresent in such a mediated context. However, communication in the digital world is still language-based, even when only in the form of written language (Koch et al., 2005).

Research on such computer-mediated communication (cmc) can be divided into different approaches. Two of them are: (1) the reduced-social-cues approach (rsc) (Sproull and Kiesler, 1986), and (2) the hyperpersonal communication approach (hp) (Walther, 1996). The first assumes that cmc filters out social context cues. The second emphasizes that cmc might surpass ftf communication, as the sender has the opportunity to optimize their self-representation while the receiver idealizes the sender on the basis of the available cues. Here lies the question whether people are able to, and actually do hide their “true selves,” that is their identity (e.g., personality), or whether they, despite being relatively anonymous, inevitably communicate aspects of their respective identity and personality that are in turn perceived by the receiver (Walther and Parks, 2002).

Sex or gender, respectively, are central features of one's identity and personality (e.g., Mealey, 2000; Ellis et al., 2008). As a matter of fact, sex has been central in cmc research. For instance, Guiller and Durndell (2007) found that in cmc men are more dominant than women, whereas women are more supportive than men—findings reminiscent of sex differences in ftf communication (Eckert and McConnell-Ginet, 2003).

A large body of research (e.g., Savicki et al., 1999; Thomson and Murachver, 2001; Koch et al., 2005) shows that only by reading text, people are able to guess the sex of the writers above chance. The same seems to be true for personality judgments (Park et al., 2015). Entire texts are not necessary, though. Lange et al. (2016b) used pseudonyms chosen by students in written exams, and had participants rate them on assumed sex of the user and other attributes. They found that sex could be guessed correctly above chance with a large effect size. Also, participants ascribed typical female and male attributes to the pseudonyms and even tried to retrieve information on the users' personality. It was also found that women, more than men, used diminutive suffixes in their pseudonyms (like -i in “cuti”). In line with these findings, Heisler and Crabill (2006) demonstrated that the majority of their participants considered themselves capable of correctly guessing the sex and age of the users of e-mail usernames. Moreover, their participants attempted to rate the supposed owners of the e-mail addresses also with respect to, among other aspects, their relationship status.

Not only is sex a matter of interest with respect to the digital world, the phenomenon of online dating is, too (Valkenburg and Peter, 2007). Considering that mate choice is one of the most important areas in social life (Buss, 2003) and that people are increasingly shifting their activities from the offline to the online world, it does not surprise that online dating has become a billion-dollar business (Sautter et al., 2010).

Human mating in general and sex differences in human mating have attracted numerous researchers and have produced a veritable deluge of related literature (e.g., Buss and Barnes, 1986; Buss, 1989; Buss and Schmitt, 1993; for an overview, see Buss, 2003, 2016; Schwarz and Hassebrauck, 2012). This research has, on the one hand, identified several characteristics that both sexes prefer in a mate (e.g., healthy), as well as those that are more preferred by women (e.g., good earning capacity, college graduate) and those more preferred by men (e.g., physically attractive) (Buss et al., 1990). The role of language in human mate choice has also been examined recently (e.g., Lange et al., 2014, 2016a). On the other hand, empirical mate choice research has documented that women are more exacting in mate choice decisions, while men face stronger same-sex competition (for an overview, see Buss, 2003). The first process, called intersexual selection, is the actual mate choice, which in most species occurs as female mate choice. That is, women because of having higher obligatory costs (Trivers, 1972), are more selective, while men, whose obligatory costs are lower, compete more strongly with other men in order to be chosen. This is called intrasexual selection (for an overview, see Buss, 2003).

Another area of interest in mate choice research is the distinction between short-term mating (the search for an affair, a one-night stand, etc.) and long-term mating (the search for a committed, steady relationship) (Buss and Schmitt, 1993), which can be referred to as a person's mating strategy (Schmitt, 2005). This distinction is somewhat linked to females being choosier than males. As the costs for males are lower than for females, men show a tendency to be relatively indiscriminate in short-term mating. A bad mate choice imposes higher costs on women than on men—and this applies more to short-term than to long-term mating. Generally, women show a preference for a long-term mate (Buss and Schmitt, 1993). As a result, men for whom short-term mating is a particularly useful strategy might want to pretend to be interested in long-term mating, while in fact they are not. Thus, women should be particularly interested in detecting a man's mating strategy (Buss, 2003).

Not only dating in general but online dating as well has excited some research interest—among others, also with respect to rsc and hp (for an overview, see Finkel et al., 2012). It has been assumed, taking the hp perspective, that the cmc limitations in online dating can be compensated by language style and choice of words (Walther et al., 2005). While physical cues are missing in cmc, the importance of verbal cues might be rising. The question then might very well be, this time with respect to online dating: what about single words instead of entire texts?

As emphasized above, communication only by means of single words is even more limited than communicating through written texts. Still, those single words might communicate crucial information (Lange et al., 2016a). In accordance with findings on mate choice in “real life,” Whitty and Buchanan (2010) found that women were more attracted to online user names (hereinafter called nicknames) (e.g., in terms of the motivation to contact the person behind the name) that signaled intelligence, while men were more attracted to nicknames indicative of physical attractiveness. So the choice of a nickname in online dating can be used for impression management—just like hp would predict. Online dating is indeed an area in the digital world in which making a good first impression is essential (Whitty and Buchanan, 2010).

Apart from classical mate choice criteria, the personality of a potential mate is crucial, too (e.g., Buss et al., 1990; Botwin et al., 1997; Escorial and Martín-Buro, 2012). In this context, research by Back et al. (2008) is particularly relevant for the research presented in the article at hand. They retrieved personality scores of 599 participants (Big Five, e.g., extraversion; narcissism) and additionally asked them for their e-mail addresses. Back et al. (2008) then presented the e-mail names to 100 participants who judged the personality dimensions of the e-mail name users on the same personality items used before. Personality dimensions were detected correctly, with results being statistically significant for all dimensions except for extraversion. Back et al. (2008) also showed that personality ratings were linked to certain attributes of the e-mail address. For instance, the perception of conscientiousness was positively correlated with both the number of characters and dots the names consisted of, while number of digits was negatively correlated with it.

The current study had the objective of replicating the findings by Back et al. (2008) with respect to online dating as well as to extend them. Back et al. (2008) used e-mail names and had a general cmc context. We, on our part, wanted to focus more on nicknames. This was inspired by research on the psychology of pseudonyms (e.g., Lange et al., 2016b) as well as based on the following assumption: While e-mail addresses are often created based on the rule “first name.last name” (e.g., john.smith@…), nicknames are assumed to be more creative (cf. Whitty and Buchanan, 2010). Also unlike Back et al. (2008), we were interested in the context of online dating and mate choice. Whitty and Buchanan (2010) have already shown that such an approach is worthwhile. Still, the scarcity of such research calls for more studies of this kind.

The question might also be asked, as to whether people are able to detect the mating strategy of a potential mate. It was also of interest whether the motivations for contacting a person behind a nickname, based only on the nickname, might differ (Whitty and Buchanan, 2010). Furthermore, we wanted additionally to investigate whether one of the two sexes are better at judging women's and men's personality based on their nicknames. Mating is an area of social life, where making a proper choice seems particularly important (Buss, 2003). So, it seemed of practical relevance to elucidate what mate choice-relevant information can be retrieved form an online dating nickname.

Finally, we were interested in the linguistic features of the nicknames, and the subsequent question whether we would find correlations between these features and other variables of interest (Back et al., 2008; Lange et al., 2016b).

We proposed the following hypothesis (cf. Back et al., 2008):

H1: People are able to correctly guess online daters' personality by means only of their nicknames. Under personality, we understood the Big Five dimensions which are: openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism (McCrae and John, 1992). The Big Five have been used quite often in research focusing on personality perceptions by means of certain cues (e.g., Küfner et al., 2010; Qui et al., 2015). As another personality dimensions, we added narcissism following the mentioned study by Back et al. (2008). Other researchers have also included this trait, which is one of three traits of the so-called Dark Triad, into their research in order to elucidate, whether it can be detected (e.g., Buffardi and Campbell, 2008; Vander Molen et al., 2018).

Furthermore, we had four research questions that were derived from mate choice research (see above) and other studies on the psychology of nicknames or usernames (Back et al., 2008; Whitty and Buchanan, 2010; Lange et al., 2016b):

RQ1: Are people able to correctly guess online daters' mating strategy by means only of their nicknames?

RQ2: What are the correlates of the motivation to contact a person behind a nickname?

RQ3: Does one sex show greater accuracy in personality judgments than the other?

RQ4: What are the linguistic correlates of the personality of the nickname users and how are they perceived? In other words, are linguistic features significant mediators of judgments?

A majority of the participants had been deceptive in therapy, and a majority were willing to be deceptive in future therapeutic contexts; participants were more likely to use white lies than other forms of deception in therapy

Deception in psychotherapy: Frequency, typology and relationship. Drew A. Curtis, Christian L. Hart. Counselling and Psychotherapy Research, September 9 2019.

Abstract: Deception in therapy has been documented anecdotally through various narratives of therapists. The investigation of its occurrence within therapy has largely been overlooked. We explored the reported frequency of deception within psychotherapy, the types of deception used within therapy, the likelihood of people lying to a therapist compared to other groups of people, and client perceptions of the types of deception that therapists use. Ninety‐one participants were provided with a series of deception examples, asked questions about the use of these types of deception within therapy, and asked generally about their use of deception in therapy. We found that a majority of the participants had been deceptive in therapy, and a majority were willing to be deceptive in future therapeutic contexts. Participants were more likely to use white lies than other forms of deception in therapy. Lastly, participants were less likely to lie to therapists compared to strangers and acquaintances. Implications for research and practice are discussed.


When people communicate with each other, there is typically a presumption of honesty; however, people lie (Levine, 2014). In classic diary studies, people report lying, on average, twice a day (DePaulo & Bell, 1996; DePaulo & Kashy, 1998; Kashy & DePaulo, 1996). However, recent research indicates that the distribution of lies is positively skewed, with a small set of people telling many lies and most people telling fewer than two lies per day (Serota & Levine, 2015). Deception takes on a variety of forms such as outright lies, exaggerations, omissions and subtle lies (DePaulo, Kashy, Kirkendol, Wyer, & Epstein, 1996; Vrij, 2000). While there are numerous forms of human deception, the common thread that ties them together is an intent to mislead others. Vrij (2008) discussed various definitions of deception that had been used in the past, noting their shortcomings. He ultimately submitted that deception is “a successful or unsuccessful deliberate attempt, without forewarning, to create in another a belief which the communicator considers to be untrue” (p. 15).
1.1 Background

Over the past several decades, there has been a tremendous amount of basic research investigating human deception (see Vrij, 2008). This research has examined deception in a variety of contexts including intimate relationships (Cole, 2001; Peterson, 1996), in the workplace (Hart, Hudson, Fillmore, & Griffith, 2006; Shulman, 2011) and in forensic areas (Granhag & Strömwall, 2004). However, the prevalence of deception within psychotherapeutic settings has been mostly overlooked. In fact, it has been suggested that “surprisingly little has been written in the counseling journals on the topic of lying” (Miller, 1992, p. 25).

While psychotherapy involves an exchange between a therapist and a client, often perceived as honest (Curtis & Hart, 2015; Kottler & Carlson, 2011), deception is occasionally found woven into components of practice. Deceitfulness is one of the criteria for antisocial personality disorder (301.7) found in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5; American Psychiatric Association; APA, 2013). The DSM‐5 also terms lying, motivated by external incentive, as malingering (V65.2). Within psychometrics, deception has been documented as a measure or scale in some assessments (e.g. Greene, 2000; Guenther & Otto, 2010). The Minnesota Multiphasic Personality Inventory‐II (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 2001) contains scales that reveal if a client is attempting to lie or be deceptive in different manners (Greene, 2000). The scant research investigating deception in therapy has focused on psychologists’ ability to detect deception, finding that counsellors and psychologists achieve 62%–85% accuracy rates when attempting to discern lies from truths, where 50% would represent chance levels of accuracy (e.g. Briggs, 1992; Ekman, O'Sullivan, & Frank, 1999). However, meta‐analyses and other literature suggest that accuracy for detecting deception is not much higher than chance for laypeople (54%) and law enforcement professionals (56%; Bond & DePaulo, 2006; Vrij, 2000).

More recently, there has been a re‐emergence of research and literature regarding deception in therapy. One study investigated therapists’ beliefs and attitudes towards client deception (Curtis & Hart, 2015). Curtis and Hart (2015) recruited 112 therapists and asked them to identify their beliefs about indicators of deception and subsequently identify their attitudes towards clients who lie. The results found that therapists possessed a number of inaccurate beliefs about actual indicators of deception (e.g. eye gaze aversion when lying), held a number of negative attitudes towards client deception (e.g. liking the client less) and lied to their clients in therapy.

While investigating psychologists’ ability to detect deception and their beliefs and attitudes towards client deception are worthwhile pursuits, the prevalence of client deception within psychotherapy has remained largely unstudied. Some literature has referenced pathological aspects of lying, termed pseudologia phantastica (e.g. Garlipp, 2017; Muzinic, Kozaric‐Kovacic, & Marinic, 2016). Additionally, in their book, Duped, Kottler and Carlson (2011) documented a number of anecdotal accounts of psychotherapists discovering that their clients had lied in therapy. Some of these reports included fabricating an entire therapy experience (Grzegorek, 2011) and intentionally omitting information about having a terminal illness (Rochlan, 2011). Thus, there is clear evidence that some clients do deceive their therapists.

Even though psychologists’ stories provide anecdotal evidence for the presence of deception within psychotherapy, there remains a dearth of empirical investigation. One recent study explored the occurrence of lying in psychotherapy, finding that 93% of 547 psychotherapy patients reported having lied to a therapist (Blanchard & Farber, 2016). Due to the present study having been conducted prior to the Blanchard and Farber (2016) study, it was not designed as a replication or intended for direct comparison.

In the current study, we sought to broaden the understanding of deception in therapy. We collected empirical data on the frequency of deception in therapy, the types of deception used and the influence of relational roles on deception. Given the previously noted research showing that many people report lying in their close relationships and in therapy, we predicted that the majority (>50%) of participants who had been in therapy would report that they had been deceptive within therapy at least once. Further, we predicted that the use of white lies and omissions would be more prevalent than other types of deception. Previous studies have found that people tell fewer lies to people with whom they are in emotionally close relationships (Vrij, 2008). Based on those findings, we predicted that participants would report being more likely to lie to a therapist than a significant other and family member, and we predicted that they would be less likely to lie to a therapist than social acquaintances and complete strangers. Based on the findings of Curtis (2013) that therapists believe clients are more likely to lie in earlier compared to later sessions, we predicted that people would report more willingness to lie to a therapist during the first session compared to subsequent sessions, due to the lack of emotional connection early in the relationship. Lastly, we predicted that people would be more likely to lie to a therapist that they did not like compared to a therapist they did like.

What are the Price Effects of Trade? Trade with China increased U.S. consumer surplus by about $400,000 per displaced job, and product categories catering to low-income consumers experienced larger price declines

What are the Price Effects of Trade? Evidence from the U.S. and Implications for Quantitative Trade Models. Xavier Jaravel, Erick Sager. Centre for Economic Policy Research, DP13902, August 2019.

Abstract: This paper finds that U.S. consumer prices fell substantially due to increased trade with China. With comprehensive price micro-data and two complementary identification strategies, we estimate that a 1pp increase in import penetration from China causes a 1.91% decline in consumer prices. This price response is driven by declining markups for domestically-produced goods, and is one order of magnitude larger than in standard trade models that abstract from strategic price-setting. The estimates imply that trade with China increased U.S. consumer surplus by about $400,000 per displaced job, and that product categories catering to low-income consumers experienced larger price declines.

Keyword(s): Markups, prices, Trade
JEL(s):     F10, F13, F14

Some Lie a Lot: Most people are fairly honest, but there are prolific liars among us

Development of the Lying in Everyday Situations Scale. Christian L Hart et al. The American Journal of Psychology 132(3):343-352, September 2019. DOI: 10.5406/amerjpsyc.132.3.0343

Abstract: Deception researchers have developed various scales that measure the use of lying in specific contexts, but there are limited tools that measure the use of lies more broadly across the various contexts of day-today life. We developed a questionnaire that assesses the use of various forms of lying, including protecting others, image enhancement, saving face, avoiding punishment, vindictiveness, privacy, entertainment, avoiding confrontation, instrumental gain, and maintaining and facilitating relationships. The results of a factor analysis brought our original 45-item scale down to a two-dimensional, 14-item scale that we have titled the Lying in Everyday Situations (LiES) scale. In three studies, the concurrent validity of the scale was assessed with several domain-specific lying scales, two Machiavellianism scales, a social desirability scale, and reports of actual lie frequency over a 24-hour period. The scale was also assessed for interitem consistency (Cronbach's α) and test-retest reliability. We found that the LiES scale was a reliable and valid measure of lying. The LiES scale may be a useful tool for assessing the general tendency to lie across various contexts.

Popular version... Some Lie a Lot: Most people are fairly honest, but there are prolific liars among us. Christian L Hart. Psychology Today, Oct 10, 2019.

Check also Deception in psychotherapy: Frequency, typology and relationship. Drew A. Curtis, Christian L. Hart. Counselling and Psychotherapy Research, September 9 2019.

And, from 2009, The Prevalence of Lying in America: Three Studies of Self‐Reported Lies. Kim B. Serota, Timothy Levine, Franklin J. Boster. Human Communication Research 36(1):2 - 25, December 2009. DOI: 10.1111/j.1468-2958.2009.01366.x
Abstract: This study addresses the frequency and the distribution of reported lying in the adult population. A national survey asked 1,000 U.S. adults to report the number of lies told in a 24-hour period. Sixty percent of subjects report telling no lies at all, and almost half of all lies are told by only 5% of subjects; thus, prevalence varies widely and most reported lies are told by a few prolific liars. The pattern is replicated in a reanalysis of previously published research and with a student sample. Substantial individual differences in lying behavior have implications for the generality of truth-lie base rates in deception detection experiments. Explanations concerning the nature of lying and methods for detecting lies need to account for this variation.
And Sexual Coercion by Women: The Influence of Pornography and Narcissistic and Histrionic Personality Disorder Traits. Abigail Hughes, Gayle Brewer, Roxanne Khan. Archives of Sexual Behavior, October 7 2019.

And “Sorry, I already have a boyfriend”: Masculine honor beliefs and perceptions of women’s use of deceptive rejection behaviors to avert unwanted romantic advances. Evelyn Stratmoen, Emilio D. Rivera, Donald A. Saucier. Journal of Social and Personal Relationships, August 7, 2019.

And Parenting by lying in childhood is associated with negative developmental outcomes in adulthood. Peipei Setoh et al. Journal of Experimental Child Psychology, September 26 2019, 104680.