Although people often value the challenge and mastery of performing an activity, their satisfaction may suffer when the tasks comprising the activity are perceived as difficult. Thus, it is important to understand the factors that influence subjective judgments of difficulty. In this research, we introduce an easily actionable and effective tactic to reduce perceptions of the overall difficulty of an activity: We find that concluding a sequence of difficult tasks with a few easy tasks can decrease perceived difficulty of the aggregate activity. While appending extra tasks to a constant sequence should increase the objective amount of effort necessary to complete all the tasks, we find that more tasks can paradoxically be perceived as less effortful. We coin this phenomenon the easy and demonstrate that it is less likely to occur when an overall activity is conceptualized as consisting of a single category rather than two distinct categories-that is, a set of difficult tasks followed by a set of easy tasks. We further show downstream consequences of this effect-through lower perceived difficulty, the easy addendum effect can lead to greater satisfaction, persistence, and more tasks performed overall. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1037/apl0001130 | DOI Listing |
BMC Genomics
January 2025
Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, No. 3888 Chenhua Road, Songjiang District, Shanghai, 201602, China.
Background: Despite the rapid advancement of high-throughput sequencing, simple sequence repeats (SSRs) remain indispensable molecular markers for various applied and research tasks owing to their cost-effectiveness and ease of use. However, existing SSR markers cannot meet the growing demand for research on lotus (Nelumbo Adans.) given their scarcity and weak connections to the lotus genome.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Sport Biomechanics, Faculty of Sports Sciences, Bu-Ali Sina University, Hamedan, Iran.
Most sports and leisure activities involve repetitive movements in the upper limb, which are typically linked to pain and discomfort in the neck and shoulder area. Movement variability is generally expressed by changes in movement parameters from one movement to another and is a time-dependent feature of repetitive activities. The purpose of this study was to examine the effect of repeated movement-induced fatigue on biomechanical coordination and variability in athletes with and without chronic shoulder pain (CSP).
View Article and Find Full Text PDFSci Rep
January 2025
General Surgery, Cancer Center, Department of Hernia Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China.
Three-dimensional (3D) printed surgical models provide an excellent surgical training option to closely mimic real operations to teach medical students who currently rely largely on visual learning aided with simple suturing pads. There is an unmet need to create simple to complex surgical training programs suitable for medical students. A prospective cohort study was conducted on a group of 16 6th year students.
View Article and Find Full Text PDFNPJ Parkinsons Dis
January 2025
Brain Electrophysiology and Epilepsy Lab (BEE-L), Epilepsy and EEG Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
We aimed to study the effect of Parkinson's disease (PD) and motor-cognitive load on the interplay between activation level and spatial complexity. To that end, 68 PD patients and 30 controls underwent electroencephalography (EEG) recording while executing visual single- and dual- Go/No-go tasks. The EEG underwent source localization, followed by parcellation of the neural activity into 116 regions of interest.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé - LIMICS, Inserm, Université Sorbonne Paris-Nord, Sorbonne Université, Paris, France.
Background: Artificial intelligence (AI) applied to real-world data (RWD; eg, electronic health care records) has been identified as a potentially promising technical paradigm for the pharmacovigilance field. There are several instances of AI approaches applied to RWD; however, most studies focus on unstructured RWD (conducting natural language processing on various data sources, eg, clinical notes, social media, and blogs). Hence, it is essential to investigate how AI is currently applied to structured RWD in pharmacovigilance and how new approaches could enrich the existing methodology.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!