Time is overestimated in obesity: A cohort study. Carmelo M Vicario et al. Journal of Health Psychology, April 16, 2019. https://doi.org/10.1177/1359105319842937
Abstract: Food addiction and high impulsivity are common traits in obesity. In accordance with the evidence that time is overestimated in patients with a history of impulsivity and/or drug addiction, we tested the hypothesis that duration is overestimated in obesity. A total of 92 obese participants and 182 healthy controls completed a timing task of visual stimuli. In line with our prediction, obese participants overestimated the duration of the displayed visual stimuli than controls. Our result has potential clinical implications in the field of obesity, as it suggests a potential contribution of this cognitive dysfunction in the emergence and maintenance of obesity-related behaviour.
Keywords: motivation, obesity, time overestimation, time processing, unhealthy lifestyle
Bipartisan Alliance, a Society for the Study of the US Constitution, and of Human Nature, where Republicans and Democrats meet.
Tuesday, April 16, 2019
As we skeptics said all along about workplace wellness programs: No effect in clinical markers of health; care spending/utilization; or absenteeism & job performance after 1.5 years
Effect of a Workplace Wellness Program on Employee Health and Economic OutcomesA Randomized Clinical Trial. Zirui Song, Katherine Baicker, JAMA. 2019;321(15):1491-1501. April 16, 2019, doi:10.1001/jama.2019.3307
Key Points
Question What is the effect of a multicomponent workplace wellness program on health and economic outcomes?
Findings In this cluster randomized trial involving 32 974 employees at a large US warehouse retail company, worksites with the wellness program had an 8.3-percentage point higher rate of employees who reported engaging in regular exercise and a 13.6-percentage point higher rate of employees who reported actively managing their weight, but there were no significant differences in other self-reported health and behaviors; clinical markers of health; health care spending or utilization; or absenteeism, tenure, or job performance after 18 months.
Meaning Employees exposed to a workplace wellness program reported significantly greater rates of some positive health behaviors compared with those who were not exposed, but there were no significant effects on clinical measures of health, health care spending and utilization, or employment outcomes after 18 months.
Abstract
Importance Employers have increasingly invested in workplace wellness programs to improve employee health and decrease health care costs. However, there is little experimental evidence on the effects of these programs.
Objective To evaluate a multicomponent workplace wellness program resembling programs offered by US employers.
Design, Setting, and Participants This clustered randomized trial was implemented at 160 worksites from January 2015 through June 2016. Administrative claims and employment data were gathered continuously through June 30, 2016; data from surveys and biometrics were collected from July 1, 2016, through August 31, 2016.
Interventions There were 20 randomly selected treatment worksites (4037 employees) and 140 randomly selected control worksites (28 937 employees, including 20 primary control worksites [4106 employees]). Control worksites received no wellness programming. The program comprised 8 modules focused on nutrition, physical activity, stress reduction, and related topics implemented by registered dietitians at the treatment worksites.
Main Outcomes and Measures Four outcome domains were assessed. Self-reported health and behaviors via surveys (29 outcomes) and clinical measures of health via screenings (10 outcomes) were compared among 20 intervention and 20 primary control sites; health care spending and utilization (38 outcomes) and employment outcomes (3 outcomes) from administrative data were compared among 20 intervention and 140 control sites.
Results Among 32 974 employees (mean [SD] age, 38.6 [15.2] years; 15 272 [45.9%] women), the mean participation rate in surveys and screenings at intervention sites was 36.2% to 44.6% (n = 4037 employees) and at primary control sites was 34.4% to 43.0% (n = 4106 employees) (mean of 1.3 program modules completed). After 18 months, the rates for 2 self-reported outcomes were higher in the intervention group than in the control group: for engaging in regular exercise (69.8% vs 61.9%; adjusted difference, 8.3 percentage points [95% CI, 3.9-12.8]; adjusted P = .03) and for actively managing weight (69.2% vs 54.7%; adjusted difference, 13.6 percentage points [95% CI, 7.1-20.2]; adjusted P = .02). The program had no significant effects on other prespecified outcomes: 27 self-reported health outcomes and behaviors (including self-reported health, sleep quality, and food choices), 10 clinical markers of health (including cholesterol, blood pressure, and body mass index), 38 medical and pharmaceutical spending and utilization measures, and 3 employment outcomes (absenteeism, job tenure, and job performance).
Conclusions and Relevance Among employees of a large US warehouse retail company, a workplace wellness program resulted in significantly greater rates of some positive self-reported health behaviors among those exposed compared with employees who were not exposed, but there were no significant differences in clinical measures of health, health care spending and utilization, and employment outcomes after 18 months. Although limited by incomplete data on some outcomes, these findings may temper expectations about the financial return on investment that wellness programs can deliver in the short term.
Introduction
Workplace wellness programs have become increasingly popular as employers have aimed to lower health care costs and improve employee health and productivity. In 2018, 82% of large firms and 53% of small employers in the United States offered a wellness program, amounting to an $8 billion industry.1,2 This growth has been aided by public investments such as the Affordable Care Act, which included funds to promote the development of workplace wellness programs.
Workplace wellness programs tend to focus on modifiable risk factors of disease, such as nutrition, physical activity, and smoking cessation. Despite widespread adoption, causal evidence of such programs’ effects on health and economic outcomes has been limited. Meta-analyses have produced varying estimates of benefits relative to costs.3-5 Observational studies have often been limited by a lack of valid control groups, selection bias, and small samples.6-8 Experimental studies of comprehensive wellness programs have been scarce and have produced mixed results, with most of the more rigorous studies now dated.9,10 Other experimental studies have focused on certain components of wellness, such as smoking cessation and weight loss, using an intervention of limited duration.11-14 A recent rigorous randomized study used individual-level rather than workplace-wide randomization, making it difficult to assess the effects of the tools used by many programs aiming to improve workplace culture or harness peer effects.15
Using a design that randomized the implementation of wellness programming at the worksite level, this study evaluated the effect of a multiyear workplace wellness program on health and economic outcomes over 18 months in a middle- and lower-income employee population at locations across the eastern United States.
Key Points
Question What is the effect of a multicomponent workplace wellness program on health and economic outcomes?
Findings In this cluster randomized trial involving 32 974 employees at a large US warehouse retail company, worksites with the wellness program had an 8.3-percentage point higher rate of employees who reported engaging in regular exercise and a 13.6-percentage point higher rate of employees who reported actively managing their weight, but there were no significant differences in other self-reported health and behaviors; clinical markers of health; health care spending or utilization; or absenteeism, tenure, or job performance after 18 months.
Meaning Employees exposed to a workplace wellness program reported significantly greater rates of some positive health behaviors compared with those who were not exposed, but there were no significant effects on clinical measures of health, health care spending and utilization, or employment outcomes after 18 months.
Abstract
Importance Employers have increasingly invested in workplace wellness programs to improve employee health and decrease health care costs. However, there is little experimental evidence on the effects of these programs.
Objective To evaluate a multicomponent workplace wellness program resembling programs offered by US employers.
Design, Setting, and Participants This clustered randomized trial was implemented at 160 worksites from January 2015 through June 2016. Administrative claims and employment data were gathered continuously through June 30, 2016; data from surveys and biometrics were collected from July 1, 2016, through August 31, 2016.
Interventions There were 20 randomly selected treatment worksites (4037 employees) and 140 randomly selected control worksites (28 937 employees, including 20 primary control worksites [4106 employees]). Control worksites received no wellness programming. The program comprised 8 modules focused on nutrition, physical activity, stress reduction, and related topics implemented by registered dietitians at the treatment worksites.
Main Outcomes and Measures Four outcome domains were assessed. Self-reported health and behaviors via surveys (29 outcomes) and clinical measures of health via screenings (10 outcomes) were compared among 20 intervention and 20 primary control sites; health care spending and utilization (38 outcomes) and employment outcomes (3 outcomes) from administrative data were compared among 20 intervention and 140 control sites.
Results Among 32 974 employees (mean [SD] age, 38.6 [15.2] years; 15 272 [45.9%] women), the mean participation rate in surveys and screenings at intervention sites was 36.2% to 44.6% (n = 4037 employees) and at primary control sites was 34.4% to 43.0% (n = 4106 employees) (mean of 1.3 program modules completed). After 18 months, the rates for 2 self-reported outcomes were higher in the intervention group than in the control group: for engaging in regular exercise (69.8% vs 61.9%; adjusted difference, 8.3 percentage points [95% CI, 3.9-12.8]; adjusted P = .03) and for actively managing weight (69.2% vs 54.7%; adjusted difference, 13.6 percentage points [95% CI, 7.1-20.2]; adjusted P = .02). The program had no significant effects on other prespecified outcomes: 27 self-reported health outcomes and behaviors (including self-reported health, sleep quality, and food choices), 10 clinical markers of health (including cholesterol, blood pressure, and body mass index), 38 medical and pharmaceutical spending and utilization measures, and 3 employment outcomes (absenteeism, job tenure, and job performance).
Conclusions and Relevance Among employees of a large US warehouse retail company, a workplace wellness program resulted in significantly greater rates of some positive self-reported health behaviors among those exposed compared with employees who were not exposed, but there were no significant differences in clinical measures of health, health care spending and utilization, and employment outcomes after 18 months. Although limited by incomplete data on some outcomes, these findings may temper expectations about the financial return on investment that wellness programs can deliver in the short term.
Introduction
Workplace wellness programs have become increasingly popular as employers have aimed to lower health care costs and improve employee health and productivity. In 2018, 82% of large firms and 53% of small employers in the United States offered a wellness program, amounting to an $8 billion industry.1,2 This growth has been aided by public investments such as the Affordable Care Act, which included funds to promote the development of workplace wellness programs.
Workplace wellness programs tend to focus on modifiable risk factors of disease, such as nutrition, physical activity, and smoking cessation. Despite widespread adoption, causal evidence of such programs’ effects on health and economic outcomes has been limited. Meta-analyses have produced varying estimates of benefits relative to costs.3-5 Observational studies have often been limited by a lack of valid control groups, selection bias, and small samples.6-8 Experimental studies of comprehensive wellness programs have been scarce and have produced mixed results, with most of the more rigorous studies now dated.9,10 Other experimental studies have focused on certain components of wellness, such as smoking cessation and weight loss, using an intervention of limited duration.11-14 A recent rigorous randomized study used individual-level rather than workplace-wide randomization, making it difficult to assess the effects of the tools used by many programs aiming to improve workplace culture or harness peer effects.15
Using a design that randomized the implementation of wellness programming at the worksite level, this study evaluated the effect of a multiyear workplace wellness program on health and economic outcomes over 18 months in a middle- and lower-income employee population at locations across the eastern United States.
Discussion
This randomized clinical trial of a multiyear,
multicomponent workplace wellness program implemented in a middle- and
lower-income population found that individuals in workplaces where the
program was offered reported better health behaviors, including regular
exercise and active weight management, but the program did not generate
differences in clinical measures of health, health care spending or
utilization, or employment outcomes after 18 months.
That the program affected self-reported health
behaviors, but not health or economic outcomes, may be interpreted in
several ways. Given that workplace wellness programs focus on changing
behavior and that behavior change may precede improvements in other
outcomes, these findings could be consistent with future improvements in
health or reductions in spending. On the other hand, behavior change is
likely easier to achieve than improvements in clinical or employment
outcomes. Thus, there may remain no detectable effects on those
outcomes, which would have implications for the return on investment in
wellness programs.
The finding of no significant effects on clinical
measures of health, health care spending, or employment outcomes is
consistent with a recent trial of a wellness program implemented at the
University of Illinois, which evaluated similar outcomes after 1 year.15
However, our study found a sizeable and robust improvement in some
self-reported health behaviors. Moreover, we found that participants did
not have lower preintervention spending than nonparticipants, although
there was selection on other dimensions. Unlike the Illinois study, this
intervention was implemented at the worksite level (rather than varying
across individuals within the same worksite), perhaps better
facilitating changes in workplace culture and providing greater social
supports for behavior change. This intervention was also fielded in a
different population, set of geographies, and employment setting,
making it difficult to isolate the causes of any differences in
findings.
These findings stand in contrast with much of the prior
literature on workplace wellness programs, which tended to find positive
and often large returns on investment through, for example, reductions
in absenteeism and health care spending.3-9,23,24
Given that most prior studies were based on observational designs with
methodological shortcomings such as potential selection bias, results
based on random assignment of the intervention are likely more reliable.
In Frontiers in Integrative Neuroscience: Emotional Theory of Rationality
Emotional Theory of Rationality. Mario Garcés and Lucila Finkel. Front. in Integrative Neuroscience, April 5 2019. https://doi.org/10.3389/fnint.2019.00011
Abstract: In recent decades, the existence of a close relationship between emotional phenomena and rational processes has certainly been established, yet there is still no unified definition or effective model to describe them. To advance our understanding of the mechanisms governing the behavior of living beings, we must integrate multiple theories, experiments, and models from both fields. In this article we propose a new theoretical framework that allows integrating and understanding the emotion–cognition duality, from a functional point of view. Based on evolutionary principles, our reasoning adds to the definition and understanding of emotion, justifying its origin, explaining its mission and dynamics, and linking it to higher cognitive processes, mainly with attention, cognition, decision-making, and consciousness. According to our theory, emotions are the mechanism for brain function optimization, aside from the contingency and stimuli prioritization system. As a result of this approach, we have developed a dynamic systems-level model capable of providing plausible explanations for certain psychological and behavioral phenomena and establishing a new framework for the scientific definition of some fundamental psychological terms.
Introduction
What is the relationship between emotion and cognition? If emotions have been historically considered as a “noisy interference” for cognitive processes (Simon, 1967), why does then emotions even exist?
Much scientific research has addressed the different areas and capabilities of the nervous system. Most of those research lines have been focused on developing models able to explain the brain’s cognitive capacities, together with its structure and dynamics at different levels (for a review see Kriegeskorte and Douglas, 2018). On the other side, emotions long stayed out of the neuroscience focus, like a collateral effect that had no easy fit within those cognitive models.
However, since the last decades of the past century, an intense debate has been active about the function and the primacy of emotion or cognition in the mental processes (Lazarus, 1984; Zajonc, 1984). These two highly polarized positions made impossible to state which of them was correct, or what was the relationship among emotion and cognition, as many necessary reasoning elements to integrate them were left apart. Wider approaches have tried to integrate both into a complete scheme (Leventhal and Scherer, 1987; de Houwer and Hermans, 2010; Gross and Barrett, 2011; Damasio and Carvalho, 2013; Li et al., 2014; Scherer and Moors, 2019), some of which have become widely spread (Moors et al., 2013), and some have been even formalized (Hudlicka, 2017; Cominelli et al., 2018). Others have also tried to derive the emotion-cognition structure from a more physiological approach (Pessoa and Adolphs, 2010; Yang et al., 2014) But until now, the exact matching between emotion and cognition has not actually been completely solved.
The main problem for the proposed models to achieve that goal is that they must clearly explain not only the dynamics of emotion-cognition interaction for the most standard behaviors but also for the most extreme ones, such as reality distortion that occurs in many pathologies like in anorexia nervosa (e.g., Body Dysmorphic Disorders). Trying to explain those extreme psychological phenomena forces the models to their limits, highlighting their structural and functional lacks and inconsistencies. Until date, none of those functional models have been able to clearly explain such phenomena from an emotion-cognition paradigm.
Finding new routes to move forward sometimes entails taking a step back and following another perspective hitherto unexplored. The numerous structures, networks, and functional levels involved in the study of the human brain require us to take that step, seek more general principles to facilitate the integration of all those elements, and deduce important implications that would otherwise go unnoticed.
In this article, we reason a new architectural framework that, while making use of simple and commonsensical elements already explored, we combine them in a different structural design, thus introducing emotions and attention as a segmentation mechanism in the information processing structure, to add to the understanding of how brain operations are optimized. This framework gives support to a new functional model which can clearly explain the existence and persistence of those extreme non-adaptive or even anti-adaptive behaviors, together with the more standard ones.
The article is divided into two complementary sections that describe the full reasoning behind the proposed model, its functional structure, and dynamics.
In the first section, we use evolutionary reasoning to find general hierarchical principles that allow us to justify the features of the nervous system and the key variables that determine the quality of its operation. We analyze the interdependence between these variables, justifying the automaticity process, and the existence of three different levels of response. We then reason the existence of intrinsic resource limitations in the system and how these limitations give rise to the attentional mechanism. From this perspective, we define the concept and role of emotions and how they control and optimize the activation and operation of advanced cognitive mechanisms.
In the second section, we analyze the structure and dynamics of the model and the interactions that occur between its different functional elements. Later, we analyze the spectrum of possible cognitive responses and how they can operate over different functional elements of the model, thus leading to different behaviors and psychological phenomena.
In this article, we explore the set of possible cognitive responses, rather than cognitive mechanisms because it is beyond the scope and length of this work and will be addressed specifically in a future article.
Abstract: In recent decades, the existence of a close relationship between emotional phenomena and rational processes has certainly been established, yet there is still no unified definition or effective model to describe them. To advance our understanding of the mechanisms governing the behavior of living beings, we must integrate multiple theories, experiments, and models from both fields. In this article we propose a new theoretical framework that allows integrating and understanding the emotion–cognition duality, from a functional point of view. Based on evolutionary principles, our reasoning adds to the definition and understanding of emotion, justifying its origin, explaining its mission and dynamics, and linking it to higher cognitive processes, mainly with attention, cognition, decision-making, and consciousness. According to our theory, emotions are the mechanism for brain function optimization, aside from the contingency and stimuli prioritization system. As a result of this approach, we have developed a dynamic systems-level model capable of providing plausible explanations for certain psychological and behavioral phenomena and establishing a new framework for the scientific definition of some fundamental psychological terms.
Introduction
What is the relationship between emotion and cognition? If emotions have been historically considered as a “noisy interference” for cognitive processes (Simon, 1967), why does then emotions even exist?
Much scientific research has addressed the different areas and capabilities of the nervous system. Most of those research lines have been focused on developing models able to explain the brain’s cognitive capacities, together with its structure and dynamics at different levels (for a review see Kriegeskorte and Douglas, 2018). On the other side, emotions long stayed out of the neuroscience focus, like a collateral effect that had no easy fit within those cognitive models.
However, since the last decades of the past century, an intense debate has been active about the function and the primacy of emotion or cognition in the mental processes (Lazarus, 1984; Zajonc, 1984). These two highly polarized positions made impossible to state which of them was correct, or what was the relationship among emotion and cognition, as many necessary reasoning elements to integrate them were left apart. Wider approaches have tried to integrate both into a complete scheme (Leventhal and Scherer, 1987; de Houwer and Hermans, 2010; Gross and Barrett, 2011; Damasio and Carvalho, 2013; Li et al., 2014; Scherer and Moors, 2019), some of which have become widely spread (Moors et al., 2013), and some have been even formalized (Hudlicka, 2017; Cominelli et al., 2018). Others have also tried to derive the emotion-cognition structure from a more physiological approach (Pessoa and Adolphs, 2010; Yang et al., 2014) But until now, the exact matching between emotion and cognition has not actually been completely solved.
The main problem for the proposed models to achieve that goal is that they must clearly explain not only the dynamics of emotion-cognition interaction for the most standard behaviors but also for the most extreme ones, such as reality distortion that occurs in many pathologies like in anorexia nervosa (e.g., Body Dysmorphic Disorders). Trying to explain those extreme psychological phenomena forces the models to their limits, highlighting their structural and functional lacks and inconsistencies. Until date, none of those functional models have been able to clearly explain such phenomena from an emotion-cognition paradigm.
Finding new routes to move forward sometimes entails taking a step back and following another perspective hitherto unexplored. The numerous structures, networks, and functional levels involved in the study of the human brain require us to take that step, seek more general principles to facilitate the integration of all those elements, and deduce important implications that would otherwise go unnoticed.
In this article, we reason a new architectural framework that, while making use of simple and commonsensical elements already explored, we combine them in a different structural design, thus introducing emotions and attention as a segmentation mechanism in the information processing structure, to add to the understanding of how brain operations are optimized. This framework gives support to a new functional model which can clearly explain the existence and persistence of those extreme non-adaptive or even anti-adaptive behaviors, together with the more standard ones.
The article is divided into two complementary sections that describe the full reasoning behind the proposed model, its functional structure, and dynamics.
In the first section, we use evolutionary reasoning to find general hierarchical principles that allow us to justify the features of the nervous system and the key variables that determine the quality of its operation. We analyze the interdependence between these variables, justifying the automaticity process, and the existence of three different levels of response. We then reason the existence of intrinsic resource limitations in the system and how these limitations give rise to the attentional mechanism. From this perspective, we define the concept and role of emotions and how they control and optimize the activation and operation of advanced cognitive mechanisms.
In the second section, we analyze the structure and dynamics of the model and the interactions that occur between its different functional elements. Later, we analyze the spectrum of possible cognitive responses and how they can operate over different functional elements of the model, thus leading to different behaviors and psychological phenomena.
In this article, we explore the set of possible cognitive responses, rather than cognitive mechanisms because it is beyond the scope and length of this work and will be addressed specifically in a future article.
Why is Productivity Correlated with Competition? Potential channels include specialization and managerial inputs
Why is Productivity Correlated with Competition? Matthew Backus. NBER Working Paper No. 25748, April 2019. https://www.nber.org/papers/w25748
Abstract: The correlation between productivity and competition is an oft–observed but ill–understood result. Some suggest that there is a treatment effect of competition on measured productivity, e.g. through a reduction of managerial slack. Others argue that greater competition makes unproductive establishments exit by reallocating demand to their productive rivals, raising observed average productivity via selection. I study the ready-mix concrete industry and offer three perspectives on this ambivalence. First, using a standard decomposition approach, I find no evidence of greater reallocation of demand to productive plants in more competitive markets. Second, I model the establishment exit decision and construct a semi-parametric selection correction to quantify the empirical significance of treatment and selection. Finally, I use a grouped IV quantile regression to test the distributional predictions of the selection hypothesis. I find no evidence for greater selection or reallocation in more competitive markets; instead, all three results suggest that measured productivity responds directly to competition. Potential channels include specialization and managerial inputs.
Abstract: The correlation between productivity and competition is an oft–observed but ill–understood result. Some suggest that there is a treatment effect of competition on measured productivity, e.g. through a reduction of managerial slack. Others argue that greater competition makes unproductive establishments exit by reallocating demand to their productive rivals, raising observed average productivity via selection. I study the ready-mix concrete industry and offer three perspectives on this ambivalence. First, using a standard decomposition approach, I find no evidence of greater reallocation of demand to productive plants in more competitive markets. Second, I model the establishment exit decision and construct a semi-parametric selection correction to quantify the empirical significance of treatment and selection. Finally, I use a grouped IV quantile regression to test the distributional predictions of the selection hypothesis. I find no evidence for greater selection or reallocation in more competitive markets; instead, all three results suggest that measured productivity responds directly to competition. Potential channels include specialization and managerial inputs.
There is evidence for a neuroticism‐related positivity bias in interpersonal perceptions (i.e., perceivers high in neuroticism tended to make more positive judgments of others’ sociability and warmth)
Neuroticism and Interpersonal Perception: Evidence for Positive, But Not Negative, Biases. Marianne Hannuschke, Mario Gollwitzer, Katharina Geukes, Mitja Back, Steffen Nestler. Journal of Personality, April 15 2019. https://doi.org/10.1111/jopy.12480
Abstract
Objective: Personality dispositions predict how individuals perceive, interpret, and react to social interactions with others. A still unresolved question is (1) whether these personality‐congruent interpersonal perceptions reflect perception biases, which occur when perceivers’ dispositions systematically predict deviations between perceivers’ and other people's perceptions of the same interaction, and/or selection effects, which occur when perceivers’ dispositions predict their selection of interaction partners, and (2) whether these effects feed back into perceivers’ personality.
Method: Data from 110 psychology freshmen involving repeated assessments of neuroticism and repeated interpersonal perceptions of social interactions with fellow students were analyzed to address these questions, focusing on neuroticism.
Results: There is evidence for a neuroticism‐related positivity bias in interpersonal perceptions (i.e., perceivers high in neuroticism tended to make more positive judgments of others’ sociability and warmth), but little evidence for personality‐congruent selection effects (i.e. neuroticism‐related preferences for interaction partners). The positivity bias did not predict intrapersonal changes in neuroticism over time, but the selection of specific interaction partners did.
Conclusions: These findings help to shed light on the interpersonal perception dynamics of neuroticism in a real‐life context and add to our understanding of the psychological mechanisms underlying the interplay of personality and interpersonal perceptions.
Abstract
Objective: Personality dispositions predict how individuals perceive, interpret, and react to social interactions with others. A still unresolved question is (1) whether these personality‐congruent interpersonal perceptions reflect perception biases, which occur when perceivers’ dispositions systematically predict deviations between perceivers’ and other people's perceptions of the same interaction, and/or selection effects, which occur when perceivers’ dispositions predict their selection of interaction partners, and (2) whether these effects feed back into perceivers’ personality.
Method: Data from 110 psychology freshmen involving repeated assessments of neuroticism and repeated interpersonal perceptions of social interactions with fellow students were analyzed to address these questions, focusing on neuroticism.
Results: There is evidence for a neuroticism‐related positivity bias in interpersonal perceptions (i.e., perceivers high in neuroticism tended to make more positive judgments of others’ sociability and warmth), but little evidence for personality‐congruent selection effects (i.e. neuroticism‐related preferences for interaction partners). The positivity bias did not predict intrapersonal changes in neuroticism over time, but the selection of specific interaction partners did.
Conclusions: These findings help to shed light on the interpersonal perception dynamics of neuroticism in a real‐life context and add to our understanding of the psychological mechanisms underlying the interplay of personality and interpersonal perceptions.
Inverse relationship between celebrity admiration and life satisfaction
Are measures of life satisfaction linked to admiration for celebrities? Mara S. Aruguete et al. Mind & Society, April 16 2019. https://link.springer.com/article/10.1007/s11299-019-00208-1
Abstract: A pattern of research findings indicates that excessive devotion to a favorite celebrity is linked to attitudes and behaviors that are psychologically unhealthy and may predict low life satisfaction. This study examines whether four common measures of life satisfaction (i.e., curiosity, meaning in life, gratitude, and flexibility) predict admiration for celebrities in two university samples and one community sample of young adults. Our results showed significant correlations between celebrity admiration and two measures of life satisfaction (curiosity and gratitude). We also found that the predictors of life satisfaction correlate with each other in ways that are consistent with previous research in positive psychology. Our research suggests an inverse relationship between celebrity admiration and life satisfaction. In addition, the results contribute to establishing the validity of four contemporary life satisfaction measures.
Keywords: Celebrity admiration Life satisfaction Meaning in life Curiosity Gratitude Flexibility
Abstract: A pattern of research findings indicates that excessive devotion to a favorite celebrity is linked to attitudes and behaviors that are psychologically unhealthy and may predict low life satisfaction. This study examines whether four common measures of life satisfaction (i.e., curiosity, meaning in life, gratitude, and flexibility) predict admiration for celebrities in two university samples and one community sample of young adults. Our results showed significant correlations between celebrity admiration and two measures of life satisfaction (curiosity and gratitude). We also found that the predictors of life satisfaction correlate with each other in ways that are consistent with previous research in positive psychology. Our research suggests an inverse relationship between celebrity admiration and life satisfaction. In addition, the results contribute to establishing the validity of four contemporary life satisfaction measures.
Keywords: Celebrity admiration Life satisfaction Meaning in life Curiosity Gratitude Flexibility
Is Apostasy Heritable? A Behavior Genetics Study — Skepticism, intolerance of contradictions?
Is Apostasy Heritable? A Behavior Genetics Study. Jason A. Freeman. Twin Research and Human Genetics, Apr 16 2019. https://doi.org/10.1017/thg.2019.4
Abstract: The present study explores whether genetic factors explain variation in the levels of apostasy — defined as a disengagement from religious belief, identity and/or practice — in a US-based sample during the transition from adolescence to early adulthood. I posit that genetic factors at least partially explain the variance of three measures of apostasy: disengagement from religious institutions, cessation of prayer and religious disaffiliation. I argue that genetic factors associated with risk-taking behaviors, externalizing behaviors and/or correlates of apostasy may all influence the likelihood of becoming an apostate during the transition from adolescence to early adulthood in the USA. Results reveal that genetic factors explain approximately 34% of the variance in cessation of prayer and 75% of the variance in religious disaffiliation. However, genetic factors do not influence disengagement from religious institutions. This study advances our knowledge of the etiology of apostasy and highlights the need to incorporate genetic data into social scientific research.
Abstract: The present study explores whether genetic factors explain variation in the levels of apostasy — defined as a disengagement from religious belief, identity and/or practice — in a US-based sample during the transition from adolescence to early adulthood. I posit that genetic factors at least partially explain the variance of three measures of apostasy: disengagement from religious institutions, cessation of prayer and religious disaffiliation. I argue that genetic factors associated with risk-taking behaviors, externalizing behaviors and/or correlates of apostasy may all influence the likelihood of becoming an apostate during the transition from adolescence to early adulthood in the USA. Results reveal that genetic factors explain approximately 34% of the variance in cessation of prayer and 75% of the variance in religious disaffiliation. However, genetic factors do not influence disengagement from religious institutions. This study advances our knowledge of the etiology of apostasy and highlights the need to incorporate genetic data into social scientific research.