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 Experiment Videos

Computerized scoring algorithms for the Autobiographical Memory Test.

Keisuke Takano1, Charlotte Gutenbrunner2, Kris Martens3

  • 1Center for Learning and Experimental Psychopathology.

Psychological Assessment
|April 4, 2017
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Usefulness of artificial intelligence in diagnosing early gastric cancer using magnifying endoscopy with narrow-band imaging.

iGIE : innovation, investigation and insights·2026
Same author

Mobile Technology for Real-Life Assessment of Positive and Negative Symptoms as well as Stress Among Individuals With Early Psychosis: A Scoping Review.

Early intervention in psychiatry·2026
Same author

Overnight negative emotion inertia is moderated by evening cortisol levels.

BMC psychology·2026
Same author

Distinct retrieval mechanisms for episodic and schematic categoric memories in depressed individuals: a re-analysis of autobiographical narratives.

Cognition & emotion·2026
Same author

Perfectionism as a transdiagnostic process in depression and generalized anxiety disorder: Evidence from a longitudinal study of young women.

Journal of anxiety disorders·2026
Same author

The Transdiagnostic Role of Emotion Regulation Difficulties and Repetitive Negative Thinking in Depression, Anxiety, and Their Comorbidity.

Depression and anxiety·2026
Same journal

Modeling of parent-rated psychopathology in children and adolescents using the Child Behavior Checklist.

Psychological assessment·2026
Same journal

Racial differences in static and dynamic sexual risk assessment instruments: Static-99R and Violence Risk Scale-Sexual Offender.

Psychological assessment·2026
Same journal

Maladaptive exercise: A psychometric investigation.

Psychological assessment·2026
Same journal

Depression and suicidal ideation and behavior measurement invariance: A comparison of foreign-born and U.S.-born service members.

Psychological assessment·2026
Same journal

Longitudinal measurement invariance and psychometric properties of the Overall Anxiety Severity and Impairment Scale (OASIS), Overall Depression Severity and Impairment Scale (ODSIS), and Positive Emotion Scale (PES) among community-dwelling adults.

Psychological assessment·2026
Same journal

Differential utility of immediate versus delayed memory measures for the identification of episodic memory impairment: Systematic review and meta-analysis.

Psychological assessment·2026
See all related articles

This study introduces automated algorithms to score autobiographical memory (AM) specificity, overcoming limitations of manual scoring in the Autobiographical Memory Test (AMT). These AI tools accurately differentiate specific from nonspecific memories in adults and youth.

Area of Science:

  • Cognitive Psychology
  • Computational Linguistics
  • Psychiatric Diagnostics

Background:

  • Reduced autobiographical memory (AM) specificity is a key feature of depressive cognition.
  • The Autobiographical Memory Test (AMT) traditionally requires manual scoring by experts, hindering large-scale research.
  • Current methods for assessing AM specificity are time-consuming and not scalable for big data analytics.

Purpose of the Study:

  • To develop and validate computerized algorithms for automatic scoring of AM specificity.
  • To adapt the AMT for automated analysis using natural language processing and machine learning.
  • To enable large-scale epidemiological studies on AM specificity in depression.

Main Methods:

  • Development of machine learning algorithms using natural language processing (NLP).

Related Experiment Videos

  • Application of algorithms to Dutch (adults) and English (youth) versions of the AMT.
  • Validation of algorithms using independent datasets and receiver operating characteristic (ROC) analysis.

    • Main Results:

    • Algorithms demonstrated high reliability in distinguishing specific from nonspecific AM (Area Under the Curve > 0.90).
    • Algorithm outputs showed a gradient reflecting memory specificity, aligning with expert judgments.
    • Successful application across both adult and youth populations for automated AM specificity scoring.

    Conclusions:

    • Computerized algorithms offer a reliable and scalable alternative to manual scoring of AM specificity.
    • These AI-driven tools can facilitate large-scale research into depressive cognition and related disorders.
    • Automated AMT scoring holds promise for advancing big data analytics in mental health research.