Dataset Information

Gain and loss learning differentially contribute to life financial outcomes.

ABSTRACT: Emerging findings imply that distinct neurobehavioral systems process gains and losses. This study investigated whether individual differences in gain learning and loss learning might contribute to different life financial outcomes (i.e., assets versus debt). In a community sample of healthy adults (n?=?75), rapid learners had smaller debt-to-asset ratios overall. More specific analyses, however, revealed that those who learned rapidly about gains had more assets, while those who learned rapidly about losses had less debt. These distinct associations remained strong even after controlling for potential cognitive (e.g., intelligence, memory, and risk preferences) and socioeconomic (e.g., age, sex, ethnicity, income, education) confounds. Self-reported measures of assets and debt were additionally validated with credit report data in a subset of subjects. These findings support the notion that different gain and loss learning systems may exert a cumulative influence on distinct life financial outcomes.

SUBMITTER: Knutson B

PROVIDER: S-EPMC3167846 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Gain and loss learning differentially contribute to life financial outcomes.

Knutson Brian B Samanez-Larkin Gregory R GR Kuhnen Camelia M CM

PloS one 20110906 9

Emerging findings imply that distinct neurobehavioral systems process gains and losses. This study investigated whether individual differences in gain learning and loss learning might contribute to different life financial outcomes (i.e., assets versus debt). In a community sample of healthy adults (n = 75), rapid learners had smaller debt-to-asset ratios overall. More specific analyses, however, revealed that those who learned rapidly about gains had more assets, while those who learned rapidly ...[more]

PMID: 21915320

Similar Datasets

Project description:Research on economic decision making has revealed specific biases in gain versus loss domains such that risky choice options are overvalued in gain conditions, implying optimism, but undervalued in loss conditions, implying pessimism. Individual differences in motivational traits and affective states have been shown to predict beliefs and behavior in risky decision making, but it is presently unclear which personal characteristics are most predictive of domain-specific biases. To address this gap in the literature, we investigated the relative influence of positive and negative motivational traits (general sensitivity to rewards and punishments) versus affective states (current levels of positive and negative emotions) on beliefs and choice behavior during a risky economic decision task. We also expanded on previous research by examining how the valence of one's judgment context (positive context tested in Experiment 1, negative context tested in Experiment 2) may determine whether risky choice behavior is more strongly influenced by positive versus negative characteristics. Biases in belief were calculated using an economic decision task that involved estimating the value of risky "stocks" relative to safe "bonds" from experienced outcomes. Experiment 1 used a positive judgment context (likelihood of a "good stock") while Experiment 2 used a negative judgment context (likelihood of a "bad stock"). Consistent with previous findings, we observed a domain-based bias in beliefs about stock values across experiments, such that participants exhibited optimism in gain domain and pessimism in the loss domain. Experiment 1 further revealed that domain-based bias and suboptimal choice behavior was predicted by trait-level reward sensitivity, while positive affective state (PAS) had a more limited influence on belief bias alone. Under the negative judgment context of Experiment 2, there was a similar relationship between reward sensitivity and choice behavior; however, results revealed a slightly stronger influence of negative affective state (NAS). A subsequent cross-study analysis found sensitivity to rewards was most predictive of domain-based biases. These results suggest that motivational traits - particularly those relating to reward sensitivity - are more consistent predictors of domain-based biases and risky choice behavior than affective states, but their predictive power depends the valence of the decision context.

Project description:Background: Changes in motor development provide children with new learning opportunities to interact with objects, their environment, and with caregivers. Previous research finds that both gross and fine motor skills are predictive of later language outcomes across early infancy and childhood. However, gross and fine motor skills afford different types of interactions. Thus, gross and fine motor skills may potentially differ in the developmental trajectories through which cascading changes in language may occur. The aim of the present study was to investigate whether there are differences in the predictive capacities of gross and fine motor skills toward language outcomes across infancy and early childhood in typical development. Method: A systematic review of existing literature on motor-language cascades was conducted in across studies measuring gross and/or fine motor and language development in children from 0 to 5 years old. Searches were conducted in PsycINFO, PubMed, and MEDLINE. Keywords used were a combination of "gross motor," "fine motor," "motor performance," "motor development," or "psychomotor development" along with "language," "language development," or "communication skills." Two independent reviewers screened abstracts and full texts based on inclusion and exclusion criteria. Results: A total of 23 articles were retained. Of these, seven studies measured only gross motor skills, four studies measured only fine motor skills, and 12 studies measured both gross and fine motor skills in the same study. Studies used a variety of measures to assess gross motor skills, fine motor skills, and language development (e.g., parent report, in lab observations, standardized assessment), and findings varied based on analyses used. Results demonstrated that both gross and fine motor skills are related to language outcomes, but due to a smaller amount of studies testing fine motor skills, conclusions regarding whether one is more important for language outcomes cannot be drawn. Conclusions: We conclude that both gross and fine motor skills help foster language development from infancy to early childhood. Limitations regarding current knowledge regarding the mechanisms that underlie motor-language cascades are discussed, as well as the need for more studies on fine motor skills.

Dataset Information

Gain and loss learning differentially contribute to life financial outcomes.

Publications

Gain and loss learning differentially contribute to life financial outcomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets