Investigating dynamics in attentive and inattentive responding together with their contextual correlates using a novel mixture IRT model for intensive longitudinal data.
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| Title: | Investigating dynamics in attentive and inattentive responding together with their contextual correlates using a novel mixture IRT model for intensive longitudinal data. |
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| Authors: | Vogelsmeier, Leonie V. D. E. (AUTHOR), Uglanova, Irina (AUTHOR), Rein, Manuel T. (AUTHOR), Ulitzsch, Esther (AUTHOR) |
| Source: | British Journal of Mathematical & Statistical Psychology. May2026, Vol. 79 Issue 2, p379-408. 30p. |
| Subjects: | Item response theory, Markov processes, Ecological momentary assessments (Clinical psychology), Measurement-model comparison, Psychometrics |
| Abstract: | In ecological momentary assessment (EMA), respondents answer brief questionnaires about their current behaviours or experiences several times per day across multiple days. The frequent measurement enables a thorough grasp of the dynamics inherent in psychological constructs, but it also increases respondent burden. To lower this burden, respondents may engage in careless and insufficient effort responding (C/IER), leaving data contaminated with responses that do not reflect what researchers want to measure. We introduce a novel approach to investigating C/IER in EMA data. Our approach combines a confirmatory mixture item response theory model separating C/IER from attentive behaviour with latent Markov factor analysis. This enables gauging the occurrence of C/IER and studying transitions among states of different response behaviours including their contextual correlates. The approach can be implemented using R packages. An empirical application showcases the approach's efficacy in pinpointing C/IER instances and gaining insights into their underlying causes. We showcase that the approach identifies various C/IER response patterns but requires heterogeneous and negatively worded items to detect straightlining. In a simulation investigating robustness against unaccounted for changes in measurement models underlying attentive responses, the approach proved robust against heterogeneity in loading patterns but not against heterogeneity in factor structures. Extensions to accommodate the latter are discussed. [ABSTRACT FROM AUTHOR] |
| Copyright of British Journal of Mathematical & Statistical Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 192937733 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Investigating dynamics in attentive and inattentive responding together with their contextual correlates using a novel mixture IRT model for intensive longitudinal data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Vogelsmeier%2C+Leonie+V%2E+D%2E+E%2E%22">Vogelsmeier, Leonie V. D. E.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Uglanova%2C+Irina%22">Uglanova, Irina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rein%2C+Manuel+T%2E%22">Rein, Manuel T.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ulitzsch%2C+Esther%22">Ulitzsch, Esther</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22British+Journal+of+Mathematical+%26+Statistical+Psychology%22">British Journal of Mathematical & Statistical Psychology</searchLink>. May2026, Vol. 79 Issue 2, p379-408. 30p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Item+response+theory%22">Item response theory</searchLink><br /><searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br /><searchLink fieldCode="DE" term="%22Ecological+momentary+assessments+%28Clinical+psychology%29%22">Ecological momentary assessments (Clinical psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement-model+comparison%22">Measurement-model comparison</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In ecological momentary assessment (EMA), respondents answer brief questionnaires about their current behaviours or experiences several times per day across multiple days. The frequent measurement enables a thorough grasp of the dynamics inherent in psychological constructs, but it also increases respondent burden. To lower this burden, respondents may engage in careless and insufficient effort responding (C/IER), leaving data contaminated with responses that do not reflect what researchers want to measure. We introduce a novel approach to investigating C/IER in EMA data. Our approach combines a confirmatory mixture item response theory model separating C/IER from attentive behaviour with latent Markov factor analysis. This enables gauging the occurrence of C/IER and studying transitions among states of different response behaviours including their contextual correlates. The approach can be implemented using R packages. An empirical application showcases the approach's efficacy in pinpointing C/IER instances and gaining insights into their underlying causes. We showcase that the approach identifies various C/IER response patterns but requires heterogeneous and negatively worded items to detect straightlining. In a simulation investigating robustness against unaccounted for changes in measurement models underlying attentive responses, the approach proved robust against heterogeneity in loading patterns but not against heterogeneity in factor structures. Extensions to accommodate the latter are discussed. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of British Journal of Mathematical & Statistical Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=192937733 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/bmsp.12373 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 379 Subjects: – SubjectFull: Item response theory Type: general – SubjectFull: Markov processes Type: general – SubjectFull: Ecological momentary assessments (Clinical psychology) Type: general – SubjectFull: Measurement-model comparison Type: general – SubjectFull: Psychometrics Type: general Titles: – TitleFull: Investigating dynamics in attentive and inattentive responding together with their contextual correlates using a novel mixture IRT model for intensive longitudinal data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Vogelsmeier, Leonie V. D. E. – PersonEntity: Name: NameFull: Uglanova, Irina – PersonEntity: Name: NameFull: Rein, Manuel T. – PersonEntity: Name: NameFull: Ulitzsch, Esther IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00071102 Numbering: – Type: volume Value: 79 – Type: issue Value: 2 Titles: – TitleFull: British Journal of Mathematical & Statistical Psychology Type: main |
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