PubMed Health⌕ Search

PubMed · 8533738

Expectations and sequelae to hypnosis: initial findings.

Abstract

As part of the introduction to an experiment using the Harvard Group Scale, subjects were given one of three brief instructions before being hypnotized: (1) no mention of negative or positive aftereffects, (2) vague warning of negative aftereffects, i.e., "some mildly unpleasant experiences", plus, "most persons report their experiences to be pleasurable and interesting", (3) specific warning of negative aftereffects, i.e., "approximately one half subjects have reported mild, short-term aftereffects such as headache", etc. (no positive information). The "specifically warned" Ss showed more negative aftereffects than both of the other groups, and the "no mention" Ss showed more than the "vaguely warned" Ss. The positive suggestions in the "vaguely warned" Ss instructions may have confounded the expectation for negative effects. A follow up study used instructions varying only in the degree of expectations for negative aftereffects (no mention of positive aftereffects). The results did not show group differences in negative aftereffects as predicted, however, correlational results suggested some interesting interactions among subject variables and the type of prehypnotic instructions administered.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

W C Coe, P Peterson, M Gwynn. 1995. Expectations and sequelae to hypnosis: initial findings.. https://doi.org/10.1080/00029157.1995.10403172

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗