dc.contributor.author | Cheng, Sophia | |
dc.contributor.author | Cohen, Alex S. | |
dc.contributor.author | Holmlund, Terje Bektesevic | |
dc.contributor.author | Foltz, Peter W. | |
dc.contributor.author | Cheng, Jian | |
dc.contributor.author | Bernstein, Jared | |
dc.contributor.author | Rosenfeld, Elizabeth | |
dc.contributor.author | Elvevåg, Brita | |
dc.date.accessioned | 2021-01-11T10:22:30Z | |
dc.date.available | 2021-01-11T10:22:30Z | |
dc.date.issued | 2020-10-06 | |
dc.description.abstract | This study examined the robustness of a traditional memory task when moved out of controlled traditional settings. A letter recall task was designed to be self-administered via a smart-device which assessed recall by participants’ writing their responses on the device. This enabled collection of both the letter recalled and the timing of this recall such that the temporal dynamics could be examined. Participants were patients with mental illness (<i>n</i>=71) and healthy volunteers (<i>n</i>=103). Temporal dynamics were examined using a new mechanism that measured memory retrieval time precisely. Data were analyzed for accuracy, time and their relationships. The classic memory phenomena and associated effects were replicated. In terms of temporal dynamics, this is the first demonstration of primacy and recency effects in time domain variables, as well as phonological similarity effects as evident by the inverted U-shaped curves in time. The speed of short-term memory processes affects accuracy, error types and timing. The robustness of these memory effects and new approach to temporal dynamics suggest this framework may be suitable for clinical applications, notably for the long-term monitoring of cognition in patients with mental illness. | en_US |
dc.identifier.citation | Cheng, Cohen, Holmlund TB, Foltz, Cheng, Bernstein, Rosenfeld, Elvevåg. A Dynamic Method, Analysis, and Model of Short-Term Memory for Serial Order with Clinical Applications. Psychiatry Research. 2020;294 | en_US |
dc.identifier.cristinID | FRIDAID 1856521 | |
dc.identifier.doi | 10.1016/j.psychres.2020.113494 | |
dc.identifier.issn | 0165-1781 | |
dc.identifier.issn | 1872-7123 | |
dc.identifier.uri | https://hdl.handle.net/10037/20255 | |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.journal | Psychiatry Research | |
dc.relation.projectID | info:eu-repo/grantAgreement/RCN/FRIMEDBIO/231395/Norway/Diagnostic support system development for the monitoring of psychosis// | en_US |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2020 The Author(s) | en_US |
dc.subject | VDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710 | en_US |
dc.subject | VDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710 | en_US |
dc.title | A Dynamic Method, Analysis, and Model of Short-Term Memory for Serial Order with Clinical Applications | en_US |
dc.type.version | publishedVersion | en_US |
dc.type | Journal article | en_US |
dc.type | Tidsskriftartikkel | en_US |
dc.type | Peer reviewed | en_US |