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A large-scale experiment on New Year's resolutions: Approach-oriented goals are more successful than avoidance-oriented goals.

ABSTRACT: Despite the popularity of New Year's resolutions, current knowledge about them is limited. We investigated what resolutions people make when they are free to formulate them, whether different resolutions reach differing success rates, and whether it is possible to increase the likelihood of a resolution's success by administering information and exercises on effective goal setting. Participants (N = 1066) from the general public were randomized into three groups: active control, some support, and extended support. The most popular resolutions regarded physical health, weight loss, and eating habits. At a one-year follow-up, 55% of responders considered themselves successful in sustaining their resolutions. Participants with approach-oriented goals were significantly more successful than those with avoidance-oriented goals (58.9% vs. 47.1%). The group that received some support was exclusively and significantly more successful compared to the other two. This study reveals that New Year's resolutions can have lasting effects, even at a one-year follow-up.

SUBMITTER: Oscarsson M

PROVIDER: S-EPMC7725288 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A large-scale experiment on New Year's resolutions: Approach-oriented goals are more successful than avoidance-oriented goals.

Oscarsson Martin M Carlbring Per P Andersson Gerhard G Rozental Alexander A

PloS one 20201209 12

Despite the popularity of New Year's resolutions, current knowledge about them is limited. We investigated what resolutions people make when they are free to formulate them, whether different resolutions reach differing success rates, and whether it is possible to increase the likelihood of a resolution's success by administering information and exercises on effective goal setting. Participants (N = 1066) from the general public were randomized into three groups: active control, some support, an ...[more]

PMID: 33296385

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Project description:Many real-world situations require navigating decisions for both reward and threat. While there has been significant progress in understanding mechanisms of decision-making and mediating neurocircuitry separately for reward and threat, there is limited understanding of situations where reward and threat contingencies compete to create approach-avoidance conflict (AAC). Here, we leverage computational learning models, independent component analysis (ICA), and multivariate pattern analysis (MVPA) approaches to understand decision-making during a novel task that embeds concurrent reward and threat learning and manipulates congruency between reward and threat probabilities. Computational modeling supported a modified reinforcement learning model where participants integrated reward and threat value into a combined total value according to an individually varying policy parameter, which was highly predictive of decisions to approach reward vs avoid threat during trials where the highest reward option was also the highest threat option (i.e., approach-avoidance conflict). ICA analyses demonstrated unique roles for salience, frontoparietal, medial prefrontal, and inferior frontal networks in differential encoding of reward vs threat prediction error and value signals. The left frontoparietal network uniquely encoded degree of conflict between reward and threat value at the time of choice. MVPA demonstrated that delivery of reward and threat could accurately be decoded within salience and inferior frontal networks, respectively, and that decisions to approach reward vs avoid threat were predicted by the relative degree to which these reward vs threat representations were active at the time of choice. This latter result suggests that navigating AAC decisions involves generating mental representations for possible decision outcomes, and relative activation of these representations may bias subsequent decision-making towards approaching reward or avoiding threat accordingly.

Project description:BACKGROUND: ESTs and full-length cDNAs represent an invaluable source of evidence for inferring reliable gene structures and discovering potential alternative splicing events. In newly sequenced genomes, these tasks may not be practicable owing to the lack of appropriate training sets. However, when expression data are available, they can be used to build EST clusters related to specific genomic transcribed loci. Common strategies recently employed to this end are based on sequence similarity between transcripts and can lead, in specific conditions, to inconsistent and erroneous clustering. In order to improve the cluster building and facilitate all downstream annotation analyses, we developed a simple genome-based methodology to generate gene-oriented clusters of ESTs when a genomic sequence and a pool of related expressed sequences are provided. Our procedure has been implemented in the software EasyCluster and takes into account the spliced nature of ESTs after an ad hoc genomic mapping. METHODS: EasyCluster uses the well-known GMAP program in order to perform a very quick EST-to-genome mapping in addition to the detection of reliable splice sites. Given a genomic sequence and a pool of ESTs/FL-cDNAs, EasyCluster starts building genomic and EST local databases and runs GMAP. Subsequently, it parses results creating an initial collection of pseudo-clusters by grouping ESTs according to the overlap of their genomic coordinates on the same strand. In the final step, EasyCluster refines the clustering by again running GMAP on each pseudo-cluster and groups together ESTs sharing at least one splice site. RESULTS: The higher accuracy of EasyCluster with respect to other clustering tools has been verified by means of a manually cured benchmark of human EST clusters. Additional datasets including the Unigene cluster Hs.122986 and ESTs related to the human HOXA gene family have also been used to demonstrate the better clustering capability of EasyCluster over current genome-based web service tools such as ASmodeler and BIPASS. EasyCluster has also been used to provide a first compilation of gene-oriented clusters in the Ricinus communis oilseed plant for which no Unigene clusters are yet available, as well as an evaluation of the alternative splicing in this plant species.

Dataset Information

A large-scale experiment on New Year's resolutions: Approach-oriented goals are more successful than avoidance-oriented goals.

Publications

A large-scale experiment on New Year's resolutions: Approach-oriented goals are more successful than avoidance-oriented goals.

Similar Datasets

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