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An implicit measure of associations with mental illness versus physical illness: response latency decomposition and stimuli differential functioning in relation to IAT order of associative conditions and accuracy

PloS one, 2014-07, Vol.9 (7), p.e101911-e101911 [Peer Reviewed Journal]

COPYRIGHT 2014 Public Library of Science ;COPYRIGHT 2014 Public Library of Science ;2014 Mannarini, Boffo. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2014 Mannarini, Boffo 2014 Mannarini, Boffo ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0101911 ;PMID: 25000406

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  • Title:
    An implicit measure of associations with mental illness versus physical illness: response latency decomposition and stimuli differential functioning in relation to IAT order of associative conditions and accuracy
  • Author: Mannarini, Stefania ; Boffo, Marilisa
  • Urgesi, Cosimo
  • Subjects: Analysis ; Attitude to Health ; Attitudes ; Biology and Life Sciences ; Categories ; Causality ; Classification ; College students ; Colleges & universities ; Computers ; Disease - psychology ; Health education ; Health literacy ; Humans ; Latency ; Mathematical models ; Measurement ; Medicine and Health Sciences ; Mental disorders ; Mental Disorders - psychology ; Mental health care ; Mental illness ; Parameters ; Physical Sciences ; Pictures ; Psychology, Social ; Semantics ; Social Sciences ; Sociology ; Stereotypes ; Stigma ; Stimuli ; Theory ; Word Association Tests ; Young Adult
  • Is Part Of: PloS one, 2014-07, Vol.9 (7), p.e101911-e101911
  • Description: The present study aimed at the definition of a latent measurement dimension underlying an implicit measure of automatic associations between the concept of mental illness and the psychosocial and biogenetic causal explanatory attributes. To this end, an Implicit Association Test (IAT) assessing the association between the Mental Illness and Physical Illness target categories to the Psychological and Biologic attribute categories, representative of the causal explanation domains, was developed. The IAT presented 22 stimuli (words and pictures) to be categorized into the four categories. After 360 university students completed the IAT, a Many-Facet Rasch Measurement (MFRM) modelling approach was applied. The model specified a person latency parameter and a stimulus latency parameter. Two additional parameters were introduced to denote the order of presentation of the task associative conditions and the general response accuracy. Beyond the overall definition of the latent measurement dimension, the MFRM was also applied to disentangle the effect of the task block order and the general response accuracy on the stimuli response latency. Further, the MFRM allowed detecting any differential functioning of each stimulus in relation to both block ordering and accuracy. The results evidenced: a) the existence of a latency measurement dimension underlying the Mental Illness versus Physical Illness - Implicit Association Test; b) significant effects of block order and accuracy on the overall latency; c) a differential functioning of specific stimuli. The results of the present study can contribute to a better understanding of the functioning of an implicit measure of semantic associations with mental illness and give a first blueprint for the examination of relevant issues in the development of an IAT.
  • Publisher: United States: Public Library of Science
  • Language: English
  • Identifier: ISSN: 1932-6203
    EISSN: 1932-6203
    DOI: 10.1371/journal.pone.0101911
    PMID: 25000406
  • Source: Open Access: PubMed Central
    DOAJ Directory of Open Access Journals
    Geneva Foundation Free Medical Journals at publisher websites
    AUTh Library subscriptions: ProQuest Central
    PLoS
    MEDLINE
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