Does Migration Make You Happy?:A Longitudinal Study of Internal Migration and Subjective Well-Being

The authors acknowledge financial support from the Economic and Social Research Council (ESRC) (RES-625-28-0001). This project is part of the ESRC Centre for Population Change (CPC). Financial support from the Marie Curie programme under the European Union's Seventh Framework Programme (FP/2007-2013) / Career Integration Grant n. PCIG10-GA-2011-303728 (CIG Grant NBHCHOICE, Neighbourhood choice, neighbourhood sorting, and neighbourhood effects).The majority of quantitative studies on the consequences of internal migration focus almost exclusively on the labour-market outcomes and the material well-being of migrants. We investigate whether individuals who migrate within the UK become happier after the move than they were before, and whether the effect is permanent or transient. Using life-satisfaction responses from twelve waves of the British Household Panel Survey and employing a fixed-effects model, we derive a temporal pattern of migrants’ subjective well-being around the time of the migration event. Our findings make an original contribution by revealing that, on average, migration is preceded by a period when individuals experience a significant decline in happiness for a variety of reasons, including changes in personal living arrangements. Migration itself causes a boost in happiness, and brings people back to their initial levels. The research contributes, therefore, to advancing an understanding of migration in relation to set-point theory. Perhaps surprisingly, long-distance migrants are at least as happy as short-distance migrants despite the higher social and psychological costs involved. The findings of this paper add to the pressure to retheorize migration within a conceptual framework that accounts for social well-being from a life-course perspective.PostprintPeer reviewe

The Bitter Truth About Sugar and Willpower: The Limited Evidential Value of the Glucose Model of Ego Depletion

This work was supported by European Research Council Grant 283849 (to N. Gold) under the European Union’s Seventh Framework Programme (FP/2007–2013)

Memory-experience gap in early adolescents' happiness reports

Studies among adult populations show that estimates of how happy one has felt in the past tend to be more positive than average happiness as assessed using time sampling techniques. This ‘memory-experience gap’ is attributed to cognitive biases, among which fading affect bias. In this paper we report a study among 352 pupils of a secondary school in the Netherlands. These youngsters reported subsequently: 1) how happy they had felt yesterday, 2) how happy they had felt during the last month, 3) what they had done the previous day and 4) how the

International Validation of a Nomogram to Predict Recurrence after Resection of Grade 1 and 2 Nonfunctioning Pancreatic Neuroendocrine Tumors

Background: Despite the low recurrence rate of resected nonfunctional pancreatic neuroendocrine tumors (NF-pNETs), nearly all patients undergo long-term surveillance. A prediction model for recurrence may help select patients for less intensive surveillance or identify patients for adjuvant therapy. The objective of this study was to assess the external validity of a recently published model predicting recurrence within 5 years after surgery for NF-pNET in an international cohort. This prediction model includes tumor grade, lymph node status and perineural invasion as predictors. Methods: Retrospectively, data were collected from 7 international referral centers on patients who underwent resection for a grade 1-2 NF-pNET between 1992 and 2018. Model performance was evaluated by calibration statistics, Harrel's C-statistic, and area under the curve (AUC) of the receiver operating characteristic curve for 5-year recurrence-free survival (RFS). A sub-analysis was performed in pNETs >2 cm. The model was improved to stratify patients into 3 risk groups (low, medium, high) for recurrence. Results: Overall, 342 patients were included in the validation cohort with a 5-year RFS of 83% (95% confidence interval [CI]: 78-88%). Fifty-eight patients (17%) developed a recurrence. Calibration showed an intercept of 0 and a slope of 0.74. The C-statistic was 0.77 (95% CI: 0.70-0.83), and the AUC for the prediction of 5-year RFS was 0.74. The prediction model had a better performance in tumors >2 cm (C-statistic 0.80). Conclusions: External validity of this prediction model for recurrence after curative surgery for grade 1-2 NF-pNET showed accurate overall performance using 3 easily accessible parameters. This model is available via www.pancreascalculator.com

Plutonium in Soils from Northeast China and Its Potential Application for Evaluation of Soil Erosion

Surface and soil core samples from northeast China were analyzed for Pu isotopes. The measured Pu-240/Pu-239 atomic ratios and Pu239 + 240/Cs-137 activity ratios revealed that the global fallout is the dominant source of Pu and Cs-137 at these sites. Migration behavior of Pu varying with land type and human activities resulted in different distribution of Pu in surface soils. A sub-surface maximum followed by exponential decline of Pu239 + 240 concentrations was observed in an undisturbed soil core, with a total Pu239 + 240 inventory of 86.9 Bq/m(2) and more than 85% accumulated in 0 similar to 20 cm layers. While only half inventory of Pu was obtained in another soil core and no sub-surface maximum value occurred. Erosion of topsoil in the site should be the most possible reason for the significantly lower Pu inventory, which is also supported by the reported Cs-137 profiles. These results demonstrated that Pu could be applied as an ideal substitute of Cs-137 for soil erosion study in the future.</p

Networks of Emotion Concepts

The aim of this work was to study the similarity network and hierarchical clustering of Finnish emotion concepts. Native speakers of Finnish evaluated similarity between the 50 most frequently used Finnish words describing emotional experiences. We hypothesized that methods developed within network theory, such as identifying clusters and specific local network structures, can reveal structures that would be difficult to discover using traditional methods such as multidimensional scaling (MDS) and ordinary cluster analysis. The concepts divided into three main clusters, which can be described as negative, positive, and surprise. Negative and positive clusters divided further into meaningful sub-clusters, corresponding to those found in previous studies. Importantly, this method allowed the same concept to be a member in more than one cluster. Our results suggest that studying particular network structures that do not fit into a low-dimensional description can shed additional light on why subjects evaluate certain concepts as similar. To encourage the use of network methods in analyzing similarity data, we provide the analysis software for free use (http://www.becs.tkk.fi/similaritynets/)