Correction to:Easy as (Happiness) Pie? A Critical Evaluation of a Popular Model of the Determinants of Well-Being (Journal of Happiness Studies, (2020), 21, 4, (1285-1301), 10.1007/s10902-019-00128-4)

In the original publication, the text (line 10) under the heading “3 Re‑examining the Numerical Estimates of the Effect of Genes and Circumstances” with sub heading “3.1 How Much Variance in Chronic Happiness Levels can be Explained by Genetic Factors?” has been published incorrectly

Easy as (Happiness) Pie? A Critical Evaluation of a Popular Model of the Determinants of Well-Being

An underlying principle behind much of the research in positive psychology is that individuals have considerable leeway to increase their levels of happiness. In an influential article that is frequently cited in support of such claims, Lyubomirsky et al. (Rev Gen Psychol 9:111–131, 2005. https://doi.org/10.1037/1089-2680.9.2.111) put forward a model (subsequently popularized under the name of the “happiness pie”) in which approximately 50% of individual differences in happiness are due to genetic factors and 10% to life circumstances, leaving 40% available to be changed via volitional activities. We re-examined Lyubomirsky et al.’s claims and found several apparent deficiencies in their chain of arguments on both the empirical and the conceptual level. We conclude that there is little empirical evidence for the variance decomposition suggested by the “happiness pie,” and that even if it were valid, it is not necessarily informative with respect to the question of whether individuals can truly exert substantial influence over their own chronic happiness level. We believe that our critical re-examination of Lyubomirsky et al.’s seminal article offers insights into some common misconceptions and pitfalls of scientific inference, and we hope that it might contribute to the construction of a more rigorous and solid empirical basis for the field of positive psychology

No Evidence That Siblings’ Gender Affects Personality Across Nine Countries

Does growing up with a sister rather than a brother affect personality? In this article, we provide a comprehensive analysis of the effects of siblings’ gender on adults’ personality, using data from 85,887 people from 12 large representative surveys covering nine countries (United States, United Kingdom, The Netherlands, Germany, Switzerland, Australia, Mexico, China, and Indonesia). We investigated the personality traits of risk tolerance, trust, patience, locus of control, and the Big Five. We found no meaningful causal effects of the gender of the next younger sibling and no associations with the gender of the next older sibling. Given the high statistical power and consistent results in the overall sample and relevant subsamples, our results suggest that siblings’ gender does not systematically affect personality

No evidence that siblings’ gender affects personality across nine countries

Does growing up with a sister rather than a brother affect personality? In this article, we provide a comprehensive analysis of the effects of siblings’ gender on adults’ personality, using data from 85,887 people from 12 large representative surveys covering nine countries (United States, United Kingdom, The Netherlands, Germany, Switzerland, Australia, Mexico, China, and Indonesia). We investigated the personality traits of risk tolerance, trust, patience, locus of control, and the Big Five. We found no meaningful causal effects of the gender of the next younger sibling and no associations with the gender of the next older sibling. Given the high statistical power and consistent results in the overall sample and relevant subsamples, our results suggest that siblings’ gender does not systematically affect personality

Life events and life satisfaction: Estimating effects of multiple life events in combined models

How do life events affect life satisfaction? Previous studies focused on a single event or separate analyses of several events. However, life events are often grouped non-randomly over the lifespan, occur in close succession, and are causally linked, raising the question of how to best analyze them jointly. Here, we used representative German data (SOEP; N = 40,121 individuals; n = 41,402 event occurrences) to contrast three fixed-effects model specifications: First, individual event models in which other events were ignored, which are thus prone to undercontrol bias; second, combined event models which controlled for all events, including subsequent ones, which may induce overcontrol bias; and third, our favored combined models that only controlled for preceding events. In this preferred model, the events of new partner, cohabitation, marriage, and childbirth had positive effects on life satisfaction, while separation, unemployment, and death of partner or child had negative effects. Model specification made little difference for employment- and bereavement-related events. However, for events related to romantic relationships and childbearing, small but consistent differences arose between models. Thus, when estimating effects of new partners, separation, cohabitation, marriage, and childbirth, care should be taken to include appropriate controls (and omit inappropriate ones) to minimize bias

Proximity can induce diverse friendships: A large randomized classroom experiment

Can outside interventions foster socio-culturally diverse friendships? We executed a large field experiment that randomized the seating charts of 182 3rd through 8th grade classrooms (N = 2,966 students) for the duration of one semester. We found that being seated next to each other increased the probability of a mutual friendship from 15% to 22% on average. Furthermore, induced proximity increased the latent propensity toward friendship equally for all students, regardless of students’ dyadic similarity with respect to educational achievement, gender, and ethnicity. However, the probability of a manifest friendship increased more among similar than among dissimilar students—a pattern mainly driven by gender. Our findings demonstrate that a scalable light-touch intervention can affect face-to-face networks and foster diverse friendships in groups that already know each other, but they also highlight that transgressing boundaries, especially those defined by gender, remains an uphill battle

Putting the self in self-correction: findings from the loss-of-confidence project

Science is often perceived to be a self-correcting enterprise. In principle, the assessment of scientific claims is supposed to proceed in a cumulative fashion, with the reigning theories of the day progressively approximating truth more accurately over time. In practice, however, cumulative self-correction tends to proceed less efficiently than one might naively suppose. Far from evaluating new evidence dispassionately and infallibly, individual scientists often cling stubbornly to prior findings. Here we explore the dynamics of scientific self-correction at an individual rather than collective level. In 13 written statements, researchers from diverse branches of psychology share why and how they have lost confidence in one of their own published findings. We qualitatively characterize these disclosures and explore their implications. A cross-disciplinary survey suggests that such loss-of-confidence sentiments are surprisingly common among members of the broader scientific population yet rarely become part of the public record. We argue that removing barriers to self-correction at the individual level is imperative if the scientific community as a whole is to achieve the ideal of efficient self-correction

Replicability, Robustness, and Reproducibility in Psychological Science

Replication—an important, uncommon, and misunderstood practice—is gaining appreciation in psychology. Achieving replicability is important for making research progress. If findings are not replicable, then prediction and theory development are stifled. If findings are replicable, then interrogation of their meaning and validity can advance knowledge. Assessing replicability can be productive for generating and testing hypotheses by actively confronting current understandings to identify weaknesses and spur innovation. For psychology, the 2010s might be characterized as a decade of active confrontation. Systematic and multi-site replication projects assessed current understandings and observed surprising failures to replicate many published findings. Replication efforts highlighted sociocultural challenges such as disincentives to conduct replications and a tendency to frame replication as a personal attack rather than a healthy scientific practice, and they raised awareness that replication contributes to self-correction. Nevertheless, innovation in doing and understanding replication and its cousins, reproducibility and robustness, has positioned psychology to improve research practices and accelerate progress