How Do Emotions Influence Saving Behavior

Employers have moved away from traditional defined benefit pension plans to defined contribution plans such as 401(k)s. As a result, many individuals are now required to make their own retirement saving and investment decisions, which has raised concerns about their ability and desire to handle these decisions. Since investment choices have major implications for future financial welfare, it is important to understand how individuals make these decisions and to identify potential ways to improve the decision-making process. Researchers have explored various factors affecting retirement saving, such as income, age, job tenure, self-control failure, financial literacy and trust. No prior research, however, has looked at the effects of emotions on retirement savings. This Issue in Brief examines how two different emotions – hope and hopefulness – affect 401(k) participation and asset allocation. The first section defines the terms. The second section describes the structure of a recent field experiment. The third section summarizes the results, which reveal that having high hope (i.e. yearning) – for a secure retirement leads to different investment behaviors than having high hopefulness (i.e. perceived likelihood). Furthermore, threats to hope and threats to hopefulness are found to have different effects on 401(k) participation and investment decisions. The final section concludes.

Understanding Hope and Its Implications for Consumer Behavior: I Hope, Therefore I Consume

Building on prior work (MacInnis and de Mello (2005) \u27The concept of hope and its relevance to product evaluation and choice\u27. Journal of Marketing 69(January), 1-14; de Mello and MacInnis (2005) \u27Why and how consumers hope: Motivated reasoning and the marketplace\u27. Inside Consumption: Consumer Motives, Goals, and Desires, S. Ratneshwar and D. G. Mick (eds.). London/New York: Routledge, pp. 44-66), the authors argue that the concept of hope is highly relevant to consumer behavior and marketing, though its study has not yet appeared in these literatures. Complicating this study is that the definition of hope across literatures is inconsistent. The purpose of this conceptual article is to articulate the concept of hope and elucidate its relevance to consumer behavior. We do so in six sections. The first section explores the conceptual meaning of hope. A definition of hope and the constituent elements that underlie it is articulated. We compare this definition to ones provided elsewhere and differentiate hope from related terms like wishing, expectations, involvement, and faith. The second section focuses on what consumers hope for. The third section considers several important consumer relevant outcomes of hope, including biased processing and self-deception, risk taking behavior, product satisfaction, and life satisfaction and materialism. The fourth section addresses the extent to which marketers are purveyors of hope and what tactics they use to induce hope in consumers. The fifth section uses the conceptualization of hope to both discuss novel ways of measuring hope and their comparisons to existing hope measures. The final section addresses a set of interesting, yet unresolved questions about hope and consumer behavior

Differentiating the Psychological Impact of Threats to Hope and Hopefulness

Recent work identifies hope as an under-explored though potentially important emotion and suggests that hope can be differentiated from an often confused construct-hopefulness. A field experiment involving 272 real world consumers investigated the effects of both hope and hopefulness on consumers' decisions and actions related to retirement investing. The results show that hope and hopefulness are two distinct emotions and have very different effects on consumers' information search, risk perceptions, and choice outcomes in retirement investment decisions, with hopefulness impacting the likelihood that consumers would invest in a 401k retirement plan and hope impacting the extent of their information search and risky decision making

Affective Forecasting and Self-Control: Why Anticipating Pride Wins Over Anticipating Shame in a Self-Regulation Context

We demonstrate that anticipating pride from resisting temptation facilitates self-control due to an enhanced focus on the self while anticipating shame from giving in to temptation results in self-control failure due to a focus on the tempting stimulus. In two studies we demonstrate the effects of anticipating pride (vs. shame) on self-control thoughts and behavior over time (Studies 1 and 2) and illustrate the process mechanism of self vs. stimulus focus underlying the differential influence of these emotions on self-control (Study 2). We present thought protocols, behavioral data (quantity consumed) and observational data (number/size of bites) to support our hypotheses

Beyond Attitudes: Attachment and Consumer Behavior

Although attachment theorists have examined the attachment concept in diverse relationship contexts (romantic relationship, kinship, and friendship, etc.), the nomological network of the construct has not been fully delineated. The purpose of the present paper is to develop this nomological network. We define brand attachment as the strength of the cognitive and emotional bond connecting the brand with the self. This definition involves two unique and essential elements: (1) connectedness between the brand and the self and (2) a cognitive and emotional bond, the strength of which evokes a readiness to allocate ones processing resources toward a brand. We examined factors that create brand attachment, the effects of brand attachment on higher order relationship-based exchange behaviors, why attachments (and hence relationships) weaken or terminate, and how they may be measured

Familial relative risks for breast cancer by pathological subtype: a population-based cohort study.

INTRODUCTION: The risk of breast cancer to first degree relatives of breast cancer patients is approximately twice that of the general population. Breast cancer, however, is a heterogeneous disease and it is plausible that the familial relative risk (FRR) for breast cancer may differ by the pathological subtype of the tumour. The contribution of genetic variants associated with breast cancer susceptibility to the subtype-specific FRR is still unclear. METHODS: We computed breast cancer FRR for subtypes of breast cancer by comparing breast cancer incidence in relatives of breast cancer cases from a population-based series with known estrogen receptor (ER), progesterone receptor (PR) or human epidermal growth factor receptor 2 (HER2) status with that expected from the general population. We estimated the contribution to the FRR of genetic variants associated with breast cancer susceptibility using subtype-specific genotypic relative risks and allele frequencies for each variant. RESULTS: At least one marker was measured for 4,590 breast cancer cases, who reported 9,014 affected and unaffected first-degree female relatives. There was no difference between the breast cancer FRR for relatives of patients with ER-negative (FRR = 1.78, 95% confidence intervals (CI): 1.44 to 2.11) and ER-positive disease (1.82, 95% CI: 1.67 to 1.98), P = 0.99. There was some suggestion that the breast cancer FRR for relatives of patients with ER-negative disease was higher than that for ER-positive disease for ages of the relative less than 50 years old (FRR = 2.96, 95% CI: 2.04 to 3.87; and 2.05, 95% CI: 1.70 to 2.40 respectively; P = 0.07), and that the breast cancer FRR for relatives of patients with ER-positive disease was higher than for ER-negative disease when the age of the relative was greater than 50 years (FRR = 1.76, 95% CI: 1.59 to 1.93; and 1.41, 95% CI: 1.08 to 1.74 respectively, P = 0.06). We estimated that mutations in BRCA1 and BRCA2 explain 32% of breast cancer FRR for relatives of patients with ER-negative and 9.4% of the breast cancer FRR for relatives of patients with ER-positive disease. Twelve recently identified common breast cancer susceptibility variants were estimated to explain 1.9% and 9.6% of the FRR to relatives of patients with ER-negative and ER-positive disease respectively. CONCLUSIONS: FRR for breast cancer was significantly increased for both ER-negative and ER-positive disease. Including receptor status in conjunction with genetic status may aid risk prediction in women with a family history.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

Background Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38–1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28–1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45–1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.Includes Cancer Research UK, Horizon 2020 and FP

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

Termite sensitivity to temperature affects global wood decay rates.

Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)-even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth's surface

Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.

UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.The Breast Cancer Association Consortium (BCAC), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL), and the Ovarian Cancer Association Consortium (OCAC) that contributed breast, prostate, and ovarian cancer data analyzed in this study were in part funded by Cancer Research UK [C1287/A10118 and C1287/A12014 for BCAC; C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, and C16913/A6135 for PRACTICAL; and C490/A6187, C490/A10119, C490/A10124, C536/A13086, and C536/A6689 for OCAC]. Funding for the Collaborative Oncological Gene-environment Study (COGS) infrastructure came from: the European Community's Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the US National Institutes of Health (CA128978) and the Post-Cancer GWAS Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112), the US Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund [with donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07)]. Additional financial support for contributing studies is documented under Supplementary Financial Support.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/2159-8290.CD-15-122