This research demonstrates that people can act more powerfully without having power. Researchers and practitioners advise people to obtain alternatives in social exchange relationships to enhance their power. However, alternatives are not always readily available, often forcing people to interact without having much power. Building on research suggesting that subjective power and objective outcomes are disconnected and that mental simulation can improve aspirations, we show that the mental imagery of a strong alternative can provide some of the benefits that real alternatives provide. We tested this hypothesis in one context of social exchange-negotiations-and demonstrate that imagining strong alternatives (vs. not) causes powerless individuals to negotiate more ambitiously. Negotiators reached more profitable agreements when they had a stronger tendency to simulate alternatives (Study 1) or when they were instructed to simulate an alternative (Studies 3-6). Mediation analyses suggest that mental simulation enhanced performance because it boosted negotiators' aspirations and subsequent first offers (Studies 2-6), but only when the simulated alternative was attractive (Study 5). We used various negotiation contexts, which also allowed us to identify important boundary conditions of mental simulations in interdependent settings: mental simulation no longer helped when negotiators did not make the first offer, when their opponents simultaneously engaged in mental simulation (Study 6), and even backfired in settings where negotiators' positions were difficult to reconcile (Study 7). An internal meta-analysis of the file-drawer produces conservative effect size estimates and demonstrates the robustness of the effect. We contribute to social power, negotiations, and mental simulation research. (PsycINFO Database Record
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http://dx.doi.org/10.1037/pspi0000129 | DOI Listing |
Neurorehabil Neural Repair
January 2025
Department of Mental and Physical Health and Preventive Medicine, University of Campania Luigi Vanvitelli, Naples, Italy.
Background And Objective: The metaverse refers to a digital realm accessible via internet connections using virtual reality and augmented reality glasses for promoting a new era of social rehabilitation. It represents the next-generation mobile computing platform expected to see widespread utilization in the future. In the context of rehabilitation, the metaverse is envisioned as a novel approach to enhance the treatment of human functioning exploiting the "synchronized brains" potential exacerbated by social interactions in virtual scenarios.
View Article and Find Full Text PDFCell
December 2024
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94143, USA; Chan Zuckerberg Biohub, San Francisco, CA 94148, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA 94115, USA. Electronic address:
Three proton-sensing G protein-coupled receptors (GPCRs)-GPR4, GPR65, and GPR68-respond to extracellular pH to regulate diverse physiology. How protons activate these receptors is poorly understood. We determined cryogenic-electron microscopy (cryo-EM) structures of each receptor to understand the spatial arrangement of proton-sensing residues.
View Article and Find Full Text PDFJ Neurosurg
January 2025
1Department of Neurosurgery, Baylor College of Medicine, Houston, Texas.
Objective: Deep brain stimulation (DBS) is an effective neurosurgical option for patients with treatment-resistant obsessive-compulsive disorder (OCD). Despite being more costly than neuroablative procedures of comparable efficacy, DBS has gained popularity over the years for its reversibility and adjustability. Although the cost-effectiveness of DBS has been investigated extensively in movement disorders, few economic analyses of DBS for psychiatric disorders exist.
View Article and Find Full Text PDFBackground: Cognitive dysfunction is central to clinicopathological models of Alzheimer's disease (AD). While AD prospective studies assess similar cognitive domains, the neuropsychological tests used vary between studies, limiting potential for aggregation. We examined a machine learning (ML) data harmonisation method for neuropsychological test data to develop a harmonised PACC score for the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) consortium.
View Article and Find Full Text PDFBackground: Predicting decline over the course of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), especially on relatively short time frames, is vital for appropriate treatment planning and to tailor patient and support systems' expectations. The current study tested if a functional upper limb motor learning task could predict one-year change in cognition and daily function.
Method: Cognitively unimpaired (n = 61), MCI (n = 35), and AD (32) older subjects (age: 74.
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