Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

Diagnostic and Statistical Manual of Mental Disorders (DSM)

1.7K
The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
1.7K
Psychosis: Goals of Pharmacotherapy01:26

Psychosis: Goals of Pharmacotherapy

663
Antipsychotic drugs are a crucial treatment method for acute and chronic psychoses, bipolar illness, and behavioral disorders. The selection of these drugs depends on several factors, including the state of the disease, clinical judgment, possible drug interactions, and the patient's sensitivity to adverse effects. In immediate scenarios, such as delirium and dementia, short-term treatment with low doses of high-potency typical or atypical agents can effectively manage symptom exacerbation.
663
Psychosis and Antipsychotic Drugs: Overview01:28

Psychosis and Antipsychotic Drugs: Overview

1.2K
The term "psychosis" refers to a spectrum of mental disorders characterized by abnormal thoughts, perceptions, and behaviors. It can manifest as mood disorders, dementia, delirium with psychotic features, substance-induced psychosis with psychotic features, brief psychotic disorder, delusional disorder, schizoaffective disorder, and schizophrenia. Among all these disorders, schizophrenia is the most common psychotic disorder, affecting 1% of the worldwide population. Psychotic...
1.2K
Psychological and Sociocultural Causes of Schizophrenia01:29

Psychological and Sociocultural Causes of Schizophrenia

853
Schizophrenia, a complex psychiatric disorder, has been historically misunderstood. Early psychological theories attributed its origins to childhood trauma and unresponsive parenting. However, contemporary research largely rejects these notions, favoring the vulnerability-stress hypothesis. This model proposes that individuals with a genetic predisposition to schizophrenia may develop the disorder following exposure to significant environmental stressors. Notably, studies on high-risk...
853

You might also read

Related Articles

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

Sort by
Same author

Blood Phenylalanine Control in Paediatric and Adult Centres in the UK: Data from 2012-2018.

Nutrients·2026
Same author

How Well Is Blood Phenylalanine Controlled in Maternal PKU in Europe? Results from 102 Pregnancies.

Nutrients·2026
Same author

The role of psychiatric-physical multimorbidity and continuity of care in seniors' medical emergency visits.

Scientific reports·2026
Same author

Delay in Diagnosis of Classical Homocystinuria.

JIMD reports·2026
Same author

From Retraumatization to Recovery: Making Acute Psychiatric Care Work for Transgender and Gender-Diverse People.

Psychiatric services (Washington, D.C.)·2026
Same author

Physician Follow-up Among Transgender and Gender Diverse Individuals after Psychiatric Emergency Department Visits and Hospitalizations: A Retrospective Population-Based Cohort Study.

Transgender health·2026

Related Experiment Video

Updated: Apr 1, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.3K

Validation of a Population-Based Algorithm to Detect Chronic Psychotic Illness.

Paul Kurdyak1, Elizabeth Lin2, Diane Green3

  • 1Director, Health Systems Research, Social and Epidemiological Research, Centre for Addiction and Mental Health, Toronto, Ontario; Lead, Mental Health and Addictions Research Program, Institute for Clinical Evaluative Sciences, Toronto, Ontario; Assistant Professor, Department of Psychiatry and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario.

Canadian Journal of Psychiatry. Revue Canadienne De Psychiatrie
|October 12, 2015
PubMed
Summary

Validating algorithms to detect chronic psychotic illness in health administrative databases is feasible. Researchers can choose methods for sensitive or specific case identification based on study needs.

More Related Videos

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis
05:52

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis

Published on: November 21, 2013

15.6K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.2K

Related Experiment Videos

Last Updated: Apr 1, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.3K
Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis
05:52

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis

Published on: November 21, 2013

15.6K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.2K

Area of Science:

  • Health services research
  • Psychiatric epidemiology
  • Data science in healthcare

Background:

  • Population-based health administrative databases are valuable for studying chronic psychotic illness.
  • Accurate case identification is crucial for reliable research outcomes.
  • Existing algorithms for detecting chronic psychotic illness in these databases require validation.

Purpose of the Study:

  • To validate algorithms for detecting individuals with chronic psychotic illness using health administrative data.
  • To assess the performance of different algorithms in terms of sensitivity, specificity, and predictive values.
  • To inform researchers on selecting appropriate case identification methods for population-based studies.

Main Methods:

  • Developed and tested 8 algorithms using hospitalization and physician service claims data from Ontario's administrative health databases (2002-2007).
  • Linked diagnostic data from 281 randomly selected psychiatric patients from Toronto hospitals to the administrative data cohort.
  • Evaluated algorithm performance using sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV).

Main Results:

  • Algorithms using only hospitalization data demonstrated higher specificity (69.9%-84.7%) and PPV (55.2%-80.8%).
  • Incorporating physician service claims increased sensitivity (90.1%-98.8%) but reduced specificity (31.1%-68.0%) and PPV (38.4%-71.1%).
  • The choice of algorithm impacts the trade-off between sensitivity and specificity.

Conclusions:

  • Health administrative data provide a feasible and valid approach for studying population-based outcomes in chronic psychotic illness.
  • Algorithm selection should align with research objectives, prioritizing either sensitivity or specificity.
  • These validated algorithms enhance the utility of administrative data for psychiatric research.