Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Deindividuation

Deindividuation

Deindividuation is a form of social influence on an individual’s behavior such that the individual engages in unusual or non-normal behavior while in a group setting. Why? Because in these group settings, the individual no longer sees themselves as an individual anymore, disinhibiting their behavior and personal restraint.

Purpose of Health Records II

Purpose of Health Records II

Health records serve various essential purposes in the healthcare system. Here are some key purposes:

Wilcoxon Signed-Ranks Test for Matched Pairs

Wilcoxon Signed-Ranks Test for Matched Pairs

The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...

Purpose of Health Records I

Purpose of Health Records I

The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:

Legal Guidelines for Documentation

Legal Guidelines for Documentation

The legal guidelines for nursing documentation are essential for ensuring accurate, professional, and ethical recording of patient care. The guidelines are discussed here:

Marcia's Theory of Identity Status

Marcia's Theory of Identity Status

James Marcia's identity status model provides a framework for understanding how adolescents navigate identity formation through varying degrees of exploration and commitment. Marcia's model builds on Erik Erikson's theories of psychosocial development, focusing specifically on how adolescents reconcile individual aspirations with societal expectations. His model describes identity formation as a dynamic process where adolescents move between different states depending on their level...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Development of a risk factor framework to inform machine learning prediction of young people's mental health problems: a Delphi study.

JAMIA open·2025

Same author

Computational modelling and neural correlates of reinforcement learning following three-week escitalopram: a double-blind, placebo-controlled semi-randomised study.

Translational psychiatry·2025

Same author

Hippocampal perineuronal net degradation identifies prefrontal and striatal circuits involved in schizophrenia-like changes in marmosets.

Science advances·2025

Same author

Machine learning for prediction of childhood mental health problems in social care.

BJPsych open·2025

Same author

Network analysis of functional disabilities and their association with mental well-being in children and adolescents: multi-country study across low- and middle-income countries.

The British journal of psychiatry : the journal of mental science·2025

Same author

Temporal trends in population attributable fractions of modifiable risk factors for dementia: a time-series study of the English Longitudinal Study of Ageing (2004-2019).

BMC medicine·2024

Search research articles

Related Experiment Video

Updated: Jul 31, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

De-identified Bayesian personal identity matching for privacy-preserving record linkage despite errors: development

Rudolf N Cardinal^1,2, Anna Moore^3,4, Martin Burchell³

¹Department of Psychiatry, University of Cambridge, Cambridge Biomedical Campus, Clifford Allbutt Building, Bay 13, Cambridge, CB2 0AH, UK. rnc1001@cam.ac.uk.

BMC Medical Informatics and Decision Making

|May 5, 2023

Summary

This study introduces a Bayesian matching technique for de-identified data linkage in epidemiological research. High accuracy is achieved without unique person identifiers, enabling secure data sharing.

Keywords:

Bayesian probabilistic linkage De-identification Electronic health records Electronic patient records Electronic medical records Identity matching Mental health Open-source software Privacy-preserving record linkage Pseudonymisation Psychiatry

More Related Videos

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

Related Experiment Videos

Last Updated: Jul 31, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

Area of Science:

Health Informatics
Epidemiology
Biostatistics

Background:

Epidemiological research necessitates linking data from multiple organizations.
Challenges include information governance for linkage without sharing identifiers and linking databases lacking common unique person identifiers.

Purpose of the Study:

To develop a Bayesian matching technique for de-identified probabilistic and deterministic data linkage.
To provide an open-source software implementation for this technique.

Main Methods:

Developed a Bayesian matching technique using fuzzy representations and handling complete mismatches.
Implemented an open-source software supporting dates of birth, names, gender, and postcodes.
Validated the technique on UK National Health Service (NHS) medical records, analyzing decision thresholds and demographic associations.

Main Results:

Achieved high accuracy in de-identified data linkage, with an area under the receiver operating curve of 0.997-0.999.
Reported a mean probability of correct linkage at 0.965 and a misidentification rate of 0.00249.
Identified demographic factors (gender, ethnicity, diagnostic codes) associated with linkage accuracy.

Conclusions:

Fully de-identified data matching with high accuracy is feasible without person-unique identifiers.
Freely available software facilitates secure and efficient data linkage for epidemiological studies.