title: Computerized scoring algorithms for the Autobiographical Memory Test.
abstract: Reduced specificity of autobiographical memories is a hallmark of depressive cognition. Autobiographical memory (AM) specificity is typically measured by the Autobiographical Memory Test (AMT), in which respondents are asked to describe personal memories in response to emotional cue words. Due to this free descriptive responding format, the AMT relies on experts' hand scoring for subsequent statistical analyses. This manual coding potentially impedes research activities in big data analytics such as large epidemiological studies. Here, we propose computerized algorithms to automatically score AM specificity for the Dutch (adult participants) and English (youth participants) versions of the AMT by using natural language processing and machine learning techniques. The algorithms showed reliable performances in discriminating specific and nonspecific (e.g., overgeneralized) autobiographical memories in independent testing data sets (area under the receiver operating characteristic curve > .90). Furthermore, outcome values of the algorithms (i.e., decision values of support vector machines) showed a gradient across similar (e.g., specific and extended memories) and different (e.g., specific memory and semantic associates) categories of AMT responses, suggesting that, for both adults and youth, the algorithms well capture the extent to which a memory has features of specific memories. (PsycINFO Database Record
authors.affiliation: Center for Learning and Experimental Psychopathology.
authors.forename: Keisuke
authors.initials: K
authors.lastname: Takano
authors.affiliation: School of Psychology, Victoria University of Wellington.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Gutenbrunner
authors.affiliation: Center for the Psychology of Learning and Experimental Psychopathology, University of Leuven.
authors.forename: Kris
authors.identifier: 0000-0002-8162-4979
authors.initials: K
authors.lastname: Martens
authors.affiliation: School of Psychology, Victoria University of Wellington.
authors.forename: Karen
authors.identifier: 0000-0003-4494-0160
authors.initials: K
authors.lastname: Salmon
authors.affiliation: Center for the Psychology of Learning and Experimental Psychopathology, University of Leuven.
authors.forename: Filip
authors.initials: F
authors.lastname: Raes
mesh_terms: D000465:Algorithms; D003071:Cognition; D060825:Cognitive Dysfunction / Q000523:psychology; D003201:Computers; D003866:Depressive Disorder / Q000523:psychology; D004644:Emotions; D006801:Humans; D007802:Language; D061212:Memory, Episodic; D011939:Mental Recall; D060388:Support Vector Machine