A sigh of relief actually confers relaxation

The Psychophysiology of the Sigh: II: The Sigh From the Psychological Perspective. Elke V lemincx, Liza Severs, Jan-Marino Ramirez. Biological Psychology, July 6 2022, 108386. https://doi.org/10.1016/j.biopsycho.2022.108386

Highlights

• Sighs have essential regulatory functions.

• Sighs may function as psychophysiological resetters.

• Sighs may contribute to psychophysiological flexibility.

Abstract

A sigh is a distinct respiratory behavior with specific psychophysiological roles. In two accompanying reviews we will discuss the physiological and psychological functions of the sigh. The present review will focus on the psychological functions of the sigh. We discuss the regulatory effects of a sigh, and argue how these effects may become maladaptive when sighs occur excessively. The adaptive role of a sigh is discussed in the context of regulation of psychophysiological states. We propose that sighs facilitate transitions from one psychophysiological state to the next, and this way contribute to psychophysiological flexibility, via a hypothesized resetting mechanism. We discuss how a sigh resets respiration, by controlling mechanical and metabolic properties of respiration associated with respiratory symptoms. Next, we elaborate on a sigh resetting emotional states by facilitating emotional transitions.

We attempt to explain the adaptive and maladaptive functions of a sigh in the framework of stochastic resonance, in which we propose occasional, spontaneous sighs to be noise contributing to psychophysiological regulation, while excessive sighs result in psychophysiological dysregulation. In this context, we discuss how sighs can contribute to therapeutic interventions, either by increasing sighs to improve regulation in case of a lack of sighing, or by decreasing sighs to restore regulation in case of excessive sighing. Finally, a research agenda on the psychology of sighs is presented.

Keywords: Sighsemotionsregulationflexibility

2. Sighing as a maladaptive behavior

Physiologically, complex breathing patterns serve to maintain blood gas levels consistent with metabolic need (Ben‐Tal & Tawhai, 2013). Breathing patterns resulting in deviations from normoxia and normocapnia, may cause respiratory symptoms. However, respiratory symptoms caused by dysfunctional breathing patterns can also occur in the presence of efficient gas exchange (Courtney and Cohen, 2006, Hornsveld et al., 1996, Hornsveld and Garssen, 1997, Vlemincx et al., 2012). While the term ‘dysfunctional breathing’ has been long used for a variety of maladaptive breathing patterns, recently, a classification system has been proposed to better understand and define dysfunctional breathing patterns (Boulding, Stacey, Niven, & Fowler, 2016). One type of dysfunctional breathing is periodic sighing (Boulding et al., 2016), also known as sigh syndrome, sighing dyspnea or sighing breathing (Aljadeff et al., 1993, Hurvitz and Weinberger, 2021, Sody et al., 2008, Wong et al., 2007, Wong et al., 2009), which consists of frequent sighing leading to hyperventilation-induced hypocapnia and associated respiratory symptoms.

Sighing more frequently than normal has been associated with various disease states. Sigh frequency in chronic low back pain patients is higher than in depressed and healthy controls, and correlates with pain ratings across periods of sitting, standing, reclining and walking (Keefe & Hill, 1985). In patients with traumatic brain injury, sighing is a frequent pain behavior, observed more during nociceptive exposure (compression of the nail bed), than during baseline, recovery and non-nociceptive exposure (non-invasive blood pressure measurements) (Nazari et al. 2018). In an ambulatory study in rheumatoid arthritis patients, sighing was associated with depression, yet not experienced pain (Robbins, Mehl, Holleran, & Kasle, 2011). Furthermore, while not a disease state, sighing is considered a symptom of motion sickness related to nausea (Leung & Hon, 2019).

In addition, sighing is associated with respiratory disease. Frequent sighing was present in a case of difficult-to-treat asthma (Prys-Picard, Kellett, & Niven, 2006). In this patient, sighs increased during exercise, and decreased after breathing retraining. In patients with respiratory disease, sighing co-occurred with emotional states (Stevenson & Ripley, 1952). In patients with so-called ‘hyperventilation syndrome’, sigh rate was higher during quiet sitting compared to healthy controls (Han et al., 1997), and while listening to soft music compared to healthy controls and asthmatics (Hormbrey, Jacobi, Patil, & Saunders, 1988).

Furthermore, the association between anxiety disorders and frequent sighing has been well established in laboratory studies; persons with panic disorder, post-traumatic stress disorder and chronic anxiety, sigh more frequently than (healthy) controls during quiet sitting and resting periods (Abelson et al., 2001, Abelson et al., 2008, Abelson et al., 2010, Blechert et al., 2007, Han et al., 1997, Schwartz et al., 1996, Tobin et al., 1983, Wilhelm et al., 2001a, Wilhelm et al., 2001b). Furthermore, the frequent sighing in panic disorder patients has been associated with chronic hypocapnia (Wilhelm et al., 2001a) and respiratory dysregulation indicated by high respiratory irregularity (Abelson et al., 2001, Martinez et al., 2001, Yeragani et al., 2002), suggesting that panic disorder patients sigh ‘excessively’ (i.e. sigh in excess of metabolic need). Importantly, however, it should be noted that these findings in anxiety disorders were observed in experimental laboratory studies, and have not been replicated in ambulatory studies. In ambulatory studies, there is no evidence that excessive sighing occurs in panic disorder (Pfaltz et al., 2009, Pfaltz et al., 2010). In addition, an ambulatory study did not find evidence for a relationship between sighing and dispositional negative emotionality (Danvers et al., 2021).

These findings could potentially, in part, be explained by the fact that ‘baselines’ or quiet sitting, resting laboratory conditions do not necessarily represent daily life (Wilhelm & Grossman, 2010). While research labs are commonly unfamiliar to participants (e.g. unfamiliar rooms, equipment, procedures, experimenters), daily life is the opposite. Previous studies have shown that panic disorder patients show increased neurobiological stress reactivity in response to contextual stressors, among which novelty (Abelson, Khan, Liberzon, & Young, 2007). Accordingly, quiet sitting and resting baseline measurements in the laboratory may constitute contextual stress or anxiety in persons with panic disorder. This reasoning would support a relationship between excessive sighing and state anxiety (which we will discuss in more detail below), rather than dispositional anxiety.

This rationale may help to understand why frequent sighing occurs in the disease states described above. We propose that the sigh is not only an important regulator of respiration (e.g. blood gases and lung compliance), but also an often overlooked contributor to the homeostatic regulation of psychological states, including stress, emotions (e.g. anxiety), and perceived symptoms and sensations (e.g. pain, dyspnea, nausea) (Vlemincx et al., 2010, Vlemincx et al., 2013). This would implicate that sighs occur frequently during these psychological states, and therefore, may become a byproduct of these psychological states associated with disease states. While sighs may be adaptive regulation mechanisms as long as their frequency matches metabolic demand, sighs may become maladaptive when occurring excessively. Excessive sighing may result in chronic hypocapnia (Wilhelm et al., 2001a), which may lead to widespread bodily symptoms (including autonomic, respiratory, cardiac, motor and emotional symptoms), overlapping with symptoms in a broad range of disease states, such as chronic pain, respiratory and cardiovascular disease, anxiety and neurological disorders. In turn, these bodily symptoms may require further regulation, and therefore further increase sighing, initiating a vicious cycle of emotions, symptoms and sighs. In other words, while sighs consistent with metabolic need may be adaptive to regulate psychological states, excessive sighs may exacerbate symptoms in various disease states. Below, we will detail the adaptive role of sighs.

Consistently over time, polygenic scores that predict higher earnings, education and health also predict lower fertility

Human Capital Mediates Natural Selection in Contemporary Humans. David Hugh-Jones & Abdel Abdellaoui. Behavior Genetics, Jul 6 2022. https://rd.springer.com/article/10.1007/s10519-022-10107-w

Abstract: Natural selection has been documented in contemporary humans, but little is known about the mechanisms behind it. We test for natural selection through the association between 33 polygenic scores and fertility, across two generations, using data from UK Biobank (N = 409,629 British subjects with European ancestry). Consistently over time, polygenic scores that predict higher earnings, education and health also predict lower fertility. Selection effects are concentrated among lower SES groups, younger parents, people with more lifetime sexual partners, and people not living with a partner. The direction of natural selection is reversed among older parents, or after controlling for age at first live birth. These patterns are in line with the economic theory of fertility, in which earnings-increasing human capital may either increase or decrease fertility via income and substitution effects in the labour market. Studying natural selection can help us understand the genetic architecture of health outcomes: we find evidence in modern day Great Britain for multiple natural selection pressures that vary between subgroups in the direction and strength of their effects, that are strongly related to the socio-economic system, and that may contribute to health inequalities across income groups.

Discussion

Previous work has documented natural selection in modern populations on variants underlying polygenic traits (Beauchamp 2016; Kong et al. 2017; Sanjak et al. 2018). We show that correlations between polygenic scores and fertility are highly concentrated among specific subgroups of the population, including people with lower income, lower education, younger first parenthood, and more lifetime sexual partners. Among mothers aged 22+, selection effects are reversed. Furthermore, the size of selection effects on a polygenic score correlates with that score’s association with labour market earnings. Strikingly, some of these results were predicted by Fisher (1930), pp. 253-254. The economic theory of fertility gives a parsimonious explanation for these findings. Because of the substitution effect of earnings on fertility, scores are selected for when they correlate with low human capital, and this effect is stronger at lower levels of income and education.

Polygenic scores which correlate with lower earnings and less education are being selected for. In addition, many of the phenotypes under positive selection are linked to disease risk. Many people would probably prefer to have high educational attainment, a low risk of ADHD and major depressive disorder, and a low risk of coronary artery disease, but natural selection is pushing against genes associated with these traits. Potentially, this could increase the health burden on modern populations, but that depends on effect sizes. Our results show that naïve estimates can be affected by sample ascertainment bias. There may be remaining sources of ascertainment bias after our weighting; if so, we expect that, like the sources of ascertainment we have controlled for, they probably bias our results towards zero. Researchers should be aware of the risks of ascertainment when studying modern natural selection.

We also do not know how estimated effect sizes of natural selection will change as more accurate polygenic scores are produced, or whether genetic variants underlying other phenotypes will show a similar pattern to those studied here. Also, effects of polygenic scores may be inflated in population-based samples, because of indirect genetic effects, gene-environment correlations, and/or assortative mating (Lee et al. 2018; Selzam et al. 2019; Kong et al. 2018; Howe et al. 2021), although we do not expect that this should change their association with number of offspring, or the resulting changes in allele frequencies. Although effects on our measured polygenic scores are small even after weighting, individually small disadvantages can cumulate to create larger effects. Lastly, note that our data comes from people born before 1970. Recent evidence suggests that fertility patterns may be changing (Doepke et al. 2022). Overall, it is probably too early to tell whether modern natural selection has a substantively important effect on population averages of phenotypes under selection.

Because selection effects are concentrated in lower-income groups, they may also increase inequality with respect to polygenic scores. For example, Figure 8 plots mean polygenic scores for educational attainment (EA3) among children from households of different income groups. The blue bars show the actual means, i.e. parents’ mean polygenic score weighted by number of children. The grey bars show the hypothetical means if all households had equal numbers of children. Natural selection against genes associated with educational attainment is stronger at the bottom of the income distribution, and this increases the differences between groups. Overall, natural selection increases the correlation of polygenic scores with income for 28 out of 33 polygenic scores, with a median percentage increase of 16.43% in the respondents’ generation (Appendix Table 5). If inequalities in polygenic scores are important for understanding social structure and mobility (Belsky et al. 2018; Rimfeld et al. 2018; Harden 2021), then these increases are substantive. Similarly, since many polygenic scores are predictive of disease risk, they could potentially increase health inequalities. In general, the evolutionary history of anatomically modern humans is related to disease risk (Benton et al. 2021); understanding the role of contemporary natural selection may help researchers to map the genetic architecture of health disparities.

Fig. 8

Mean polygenic score for educational attainment (EA3) of children by household income group. Blue is actual. Grey is hypothetical in the absence of selection effects (Color figure online)

Full size image

Existing evidence on human natural selection has led some to “biocosmic pessimism” (Sarraf and Feltham 2019). Others are more sanguine, and argue that natural selection’s effects are outweighed by environmental improvements, like those underlying the Flynn effect (Flynn 1987). The evidence here may add some nuance to this debate. Patterns of natural selection have been relatively consistent across the past two generations, but they are not the outcome of a single, society-wide phenomenon. Instead they result from opposing forces, operating in different parts of society and pulling in different directions.

Any model of fertility is implicitly a model of natural selection, but so far, the economic and human genetics literatures have developed in parallel. Integrating the two could deepen our understanding of natural selection in modern societies. Economics possesses a range of theoretical models on the effects of skills, education and income (see Hotz et al. 1997; Lundberg and Pollak 2007). One perennial problem is how to test these theories in a world where education, labour and marriage markets all interact. Genetic data, such as polygenic scores, could help to pin down the direction of causality, for example via Mendelian randomization (Smith and Shah 2003). Conversely, economic theories and empirical results can shine a light on the mechanisms behind natural selection, and thereby on the nature of individual differences in complex traits and disease risk.

For both women and men, higher education predicted a high masturbation frequency and sexual dissatisfaction

A Seemingly Paradoxical Relationship Between Masturbation Frequency and Sexual Satisfaction. Nantje Fischer & Bente Træen. Archives of Sexual Behavior, Jul 5 2022. https://rd.springer.com/article/10.1007/s10508-022-02305-8

Abstract: Despite many benefits related to masturbation, we know surprisingly little about how solo sex is associated with sexual satisfaction. Using questionnaire data from a probability-based sample of 4,160 Norwegians aged 18–89 years, we explored subgroups of women and men that differed in their masturbation–sexual satisfaction typology and examined whether sociodemographic, psychological, and sexual behavioral characteristics were associated with distinct masturbation–satisfaction patterns. A cluster analysis revealed four similar groupings for women and men, reflecting sex lives characterized by high masturbation/sexual satisfaction, low masturbation/sexual satisfaction, high masturbation/sexual dissatisfaction, or low masturbation/sexual dissatisfaction. While being younger, higher pornography consumption, and sexual variety were primarily associated with increased masturbation frequency, sexual distress and a negative body and genital self-image were more clearly associated with sexual dissatisfaction. Predicting different masturbation–satisfaction groupings also revealed some gender-specific findings in the use of pornography, and in the association between masturbation and intercourse frequency, which suggested a complementary pattern for women and a compensatory pattern for men. Our findings emphasize that the linkage between masturbation and sexual satisfaction warrants closer focus.

Discussion

Previous studies have focused on linear relationships between sexual satisfaction and masturbation frequency, without considering the possibility that women and men might vary in their masturbation–sexual satisfaction relationships. The clustering in this study revealed four groupings, with men’s and women’s sex life being characterized by either HmS, LmS, HmD, or LmD. Further, we assessed whether sociodemographic, psychological, and sexual behavioral factors predicted distinct masturbation–satisfaction patterns.

Two interesting patterns emerged. Psychological factors (sexual distress, body image and genital self-image) were more clearly related to sexual dissatisfaction, while age and sexual behavioral factors (pornography use, sexual experience and desires) were mainly linked to masturbation frequency. A possible reason for the fragmented findings may reflect that masturbatory behavior only partly contributes to a person’s overall sex life satisfaction. For example, Philippsohn and Hartmann (2009) found that masturbation was considerably less central in explaining women’s overall sexual satisfaction than sexual intercourse activity. Moreover, qualitative data from focus groups with 50 heterosexual men reveal that, compared to partnered sexual activities, masturbation was not fully integrated into men’s sense of being sexual (Janssen et al., 2008). These studies indicate that, although overlapping, sexual satisfaction from solitary and partnered sexuality might be different. Similarly, qualitative data from focus groups with 73 queer and heterosexual women showed that solitary and partnered sexual pleasure were largely distinct constructs, with only some overlap (Goldey et al., 2016). Future studies should therefore consider defining and measuring solitary and partnered sex life satisfaction as distinct concepts.

A Compensatory or Complementary Pattern?

Women with higher sexual intercourse frequency were more likely to report high masturbation and satisfaction (HmS) than any other group (LmS, HmD, LmD). Also, more sexual experimentation among women was associated with more masturbation and satisfaction (HmS), compared to participants with LmS. Both findings support a complementary pattern for women, as it implies that frequent solo sex enhances partnered sex and is more widespread among adults with a sexualized personality pattern (e.g., increased sexual experimentation and desires) (Das et al., 2009).

Similar as in women, we found that men with higher intercourse frequency were more likely to be sexually satisfied (HmS), than those belonging to a sexually dissatisfied cluster (HmD or LmD). This is a finding that corresponds to previous studies that have found a positive relationship between partnered sex and sexual satisfaction (Brody & Costa, 2009; Byers & Rehman, 2014; Schoenfeld et al., 2017). However, when comparing men with high sexual satisfaction (HmS versus LmS), those with more partnered sex were more likely to report no or low masturbation (LmS). This finding supports a compensatory pattern in men, as it suggests that masturbation is regarded as unnecessary if one has highly satisfying and frequent sex with a partner (Regnerus et al., 2017). The gendered finding, revealing a compensatory pattern among men and a complementary pattern among women, is consistent with prior work supporting gender-specific models (Carvalheira & Leal, 2013; Fischer et al., 2022; Gerressu et al., 2008; Regnerus et al., 2017).

Pornography Use Predict HmS

Another notable finding was that both women and men with frequent pornography use were more likely to report high masturbation and sexual satisfaction (HmS) than those belonging to a cluster characterized by no or low masturbation (LmS or LmD). This finding is similar to previous studies that have found a positive relationship between pornography use and masturbation (Baćak & Štulhofer, 2011; Carvalheira et al., 2015; Richters et al., 2014) and emphasizes that pornography functions as an aid for masturbation (Prause, 2019).

Apart from this, we found a link between pornography use, high masturbation, and sexual satisfaction in men (but not in women). When comparing men characterized by relatively high masturbation frequency (HmD vs. HmS), those with greater pornography use were more likely to report being sexually dissatisfied (HmD). This finding is consistent with a recent meta-analysis (Wright et al., 2017), which documented a negative association between men’s pornography use and sexual satisfaction, but no overall or global association between women’s pornography consumption and sexual satisfaction.

Evaluative Factors Associated with Specific Masturbation-Satisfaction Typologies

Among both genders, a more negative body image was associated with being sexually dissatisfied (HmD in women and men; LmD in women), compared to participants in the reference cluster (HmS). This is consistent with previous evidence, implicating important links between body image and sexual satisfaction (Træen et al., 2016; Woertman & van den Brink, 2012). Interestingly, genital self-image was only linked to male cluster’s. In particular, a negative genital self-image was associated with being sexually dissatisfied (HmD and LmD), compared to the reference cluster (HmS). These findings echo those of a recent study, which revealed that when accounting for all body attitudes (body fat, genitals, muscularity, and height), only negative attitudes toward one’s own genitals were significantly associated with sexual dissatisfaction in men (van den Brink et al., 2018). The fact that men’s genitalia play an important role in defining masculinity in terms of appearance (e.g., penis size) and performance (e.g., erection) might explain the influences of men’s genital self-image on their sexual satisfaction.

Another central finding of the present study was that women and men who experienced distressing sexual problems were more likely to be dissatisfied with their sex life (HmD and LmD), compared to the reference cluster (HmS). This is in line with previous research indicating that sexual distress and sexual satisfaction are closely related (Stephenson & Meston, 2010).

Links Between Sociodemographic Factors and Masturbation-Satisfaction Typologies

Some sociodemographic factors predicted specific masturbation-satisfaction typologies. Interestingly, although accounting for sexual intercourse frequency, relationship status remained an important predictor of high masturbation frequency and sexual satisfaction. Specifically, those who were married/cohabitant or in a registered partnership were less likely to report high masturbation and satisfaction than falling into a cluster characterized by LmS, HmD, LmD. This resembles findings of a recent large-scale study, which documented a negative association between being partnered and recent masturbation (Regnerus et al., 2017). As Regnerus et al. controlled for sexual frequency and sexual contentment, this was a surprising finding, providing “evidence that the effect of partnered status is not simply the effect of stable access to sex” (p. 2117).

For both women and men, higher education predicted a high masturbation frequency and sexual dissatisfaction (HmD). This finding dovetails with previous findings documenting a positive relationship between higher education and more masturbation (Gerressu et al., 2008; Kaminsky-Bayer, 2020; Kontula & Haavio-Mannila, 2003; Richters et al., 2014). However, previous research also seems to indicate that education does not play a major role in sexual satisfaction (Byers & Rehman, 2014). It is thus unclear why higher education was related to less sexual satisfaction among those who frequently masturbate. Finally, consistent with prior studies on age-related decreases in masturbation activity (Fischer et al., 2022; Lee et al., 2016; Schick et al., 2010a, 2010b), older age was related with a sex life characterized by low masturbation (LmS in women and men; LmD in men).

Implications

The clusters characterized by no or low masturbation frequency and sexual satisfaction (HmS) were the largest clusters in both genders. This is interesting and may changes supposing the sexual scripts toward masturbation become more pronounced and positive in the future. The smallest clusters were those that included individuals dissatisfied with their sex life (HmD and LmD). To create a more masturbation-friendly society, future sexual health initiatives should focus on promoting masturbation and positive attitudes toward masturbation (Kontula & Haavio-Mannila, 2003).

Study Limitations

Several limitations should be addressed. First, the item used to assess masturbation frequency lacked an explicit definition and contextualization of the term masturbation. As the measure does not solely refer to masturbation in unpartnered situations, it is possible that participants used varied definitions when responding to the question. Accordingly, we cannot rule out that some also referred to masturbation during sexual intercourse. However, recent evidence indicates that the common script for sexual self-pleasure incorporates solo rather than partnered masturbation (Kirschbaum & Pederson, 2018). Specifically, the absence of a partner and having an orgasm seem to be central aspects of labeling a sexual act as masturbation. Second, although the use of single-item indicators is standard practice and indicates good convergent validity with sexual satisfaction scales (Mark et al., 2014; Štulhofer et al., 2010), the psychometric properties of multiple-item scales are preferable. However, because many individuals seem to fill out online questionnaires on their mobile phones (in this study 51%), we had to prioritize single items to minimize response fatigue. Third, no information about attitudes toward masturbation and feelings associated with sexual self-pleasure was collected. Thus, third-variable problems cannot be ruled out. Assessing negative and positive perceptions of masturbation would have allowed for more differentiated clustering. Another limitation pertains the presumption of binary gender/sex in some questions. Also, because the results from this study are based on cross-sectional data, it is not feasible to draw any causal conclusions. Further, the possibility of social desirability bias and volunteer bias may affect our findings and limit the generalizability of the study findings (Boughner, 2010). A final limitation pertains to the low response rate. In the past decades, scientific research has experienced a steady decrease in participation rates (Galea & Tracy, 2007). This applies also to Norwegian surveys, where response rates have been declining from 63% in 1987, to 48% in 1992, 38% in 1997, 34% in 2002, and 23% in 2008 (Træen & Stigum, 2010). One reason for much higher refusal rates nowadays may be the growing number of instances people are asked to participate in studies (Galea & Tracy, 2007). Because this survey was carried out during the COVID-19-related lockdown, which was imposed on 12 March in Norway, it is possible that some Web Panel members were less receptive to participate in a study on sexual behavior. Moreover, it is uncertain how the COVID-19-related restrictions may have influenced our findings. Another explanation for the low response rate may pertain to the length of the questionnaire. According to Kantar, response rates for surveys drawn from the Gallup Panel vary between 46 and 51%. An estimated timeframe of 15–20 min for our survey was probably too long, especially because 51% of the respondents were answering on their mobile devices.

Openness to experience, extraversion and neuroticism correlated with a higher frequency of sexual dreams; agreeableness showed a negative relationship

Personality correlates of the self-rated frequency of erotic dreams. Anja S. Göritz. International Journal of Dream Research, Vol 15, No 1 (April 2022). https://doi.org/10.11588/ijodr.2022.1.86903

Abstract: Erotic dreams have been of interest for researchers and the public alike. Although, the gender difference in the frequency of erotic dreams is well documented with men reporting erotic dreams more often than women, studying other factors, for example, personality traits, in relationship with erotic dreaming is scarce. Overall, 1711 participant estimated the percentage of erotic dreams with regard to all their remembered dreams and also completed a Big Five Personality inventory. The findings indicate that four of the Big Five personality factors were related to the frequency of erotic dreams; although the effects sizes of these associations were small. As expected, openness to experience correlated with a higher frequency of sexual dreams, as this personality trait is related to more frequent positive sexual cognitions and pornography consumption. Whereas extraversion and neuroticism were also positively related to erotic dream frequency, agreeableness showed a negative relationship. These kinds of studies help to understand how waking life sexuality affect erotic dreams, and in more general terms, how waking life is reflected in dreams.

Toward a Deeper Understanding of Prolific Lying: The more that people lied, the more they believed that others lied as well

Toward a Deeper Understanding of Prolific Lying: Building a Profile of Situation-Level and Individual-Level Characteristics. David M. Markowitz. Communication Research, July 4, 2022. https://doi.org/10.1177/00936502221097041

Abstract: Prior work suggests those who lie prolifically tend to be younger and self-identify as male compared to those who engage in everyday lying, but little research has developed an understanding of prolific lying beyond demographics. Study 1 (N = 775) replicated the prior demographic effects and assessed prolific lying through situation-level (e.g., opportunistic cheating) and individual-level characteristics (e.g., dispositional traits, general communication patterns) for white and big lies. For these two lie types, prolific lying associated with more opportunistic cheating, the use of fewer adjectives, and being high on psychopathy compared to everyday lying. Study 2 (N = 1,022) replicated these results and observed a deception consensus effect reported in other studies: the more that people deceived, the more they believed that others deceived as well. This piece develops a deeper theoretical understanding of prolific lying for white and big lies, combining evidence of situational, dispositional, and communication characteristics.

Keywords: lying, deception, prolific lying, automated text analysis, Dark Triad, deception consensus effect

The Effect of Labor Market Liberalization on Political Behavior and Free Market Norms: The kibbutz liberalization in the 1990s

The Effect of Labor Market Liberalization on Political Behavior and Free Market Norms. Ran Abramitzky, Netanel Ben-Porath, Shahar Lahad, Victor Lavy & Michal Palgi. NBER Working Paper 30186, Jun 2022. DOI 10.3386/w30186

Abstract: We study the effects of labor market liberalization on political behavior and attitudes towards free-market capitalism and socialism, exploiting a reform whereby the Israeli socialist communities called kibbutzim shifted from equal sharing to market-based wages. Our identification strategy relies on this reform's sharp and staggered implementation in different kibbutzim. We first examine changes in behavior associated with this labor market liberalization and document that the reform led to a shift in electoral voting patterns, resulting in decreased support for left-wing political parties and increased support for the center and right parties in national elections. Using annual survey data on attitudes over 25 years, we show that the reform led to increased support for free-market policies such as full privatization and differential wages. Moreover, it decreased support for socialist policies such as the joint ownership of production means. Yet, the reform increased support for the safety net to support weak members through mutual guarantee. These effects appear to be driven by an increase in living standards and work ethics that resulted from the reform. We conclude that introducing market-based wages led to a shift in attitudes towards a market economy with compassion, revealing a change in members’ support from their traditional democratic socialist model to a social democratic model.

Political Conservatives and Political Liberals Have Similar Views about the Goodness of Human Nature

Political Conservatives and Political Liberals Have Similar Views about the Goodness of Human Nature. Eric Schwitzgebel with Nika Chegenizadeh. Monday, July 04, 2022. schwitzsplinters.blogspot.com/2022/07/political-conservatives-and-political.html

Back in 2007, I hypothesized that political liberals would tend to have more positive views about the goodness of human nature than political conservatives. My thinking was grounded in a particular conception of what it is to say that "human nature is good". Drawing on Mengzi and Rousseau (and informed especially by P.J. Ivanhoe's reading of Mengzi), I argued that those who say human nature is good have a different conception of moral development than do those who say it is bad.

[...]

Those who say human nature is bad have, in contrast, an outward-in model of moral development. On this view, what is universal to humans is self-interest. Morality is an artificial social construction. Any quiet voice of conscience we might have is the result of cultural learning. People regularly commit evil and feel perfectly fine about it. Moral development proceeds by being instructed to follow norms that at first feel alien and unpleasant -- being required to share your toys, for example. Eventually you can learn to conform whole-heartedly to socially constructed moral norms, but this is more a matter of coming to value what society values than building on any innate attraction to moral goodness.

Thus, a liberal style of caregiving, which emphasizes children exploring their own values, fits nicely with the view that human nature is good, while a conservative style of caregiving, which emphasizes conformity to externally imposed rules, fits nicely with the view that human nature is bad.

Data: Schwitzgebel, Eric. 2022. “Do Political Liberals Have More Optimistic Views about the Goodness of Human Nature?” OSF. June 27. osf.io/ys6nj