The DOI matches its Crossref record; 109 of the 111 references it cites were found in a registry or an index.
Individual differences in cognitive plasticity: an investigation of training curves in younger and older adults.
Abstract
To date, cognitive intervention research has provided mixed but nevertheless promising evidence with respect to the effects of cognitive training on untrained tasks (transfer). However, the mechanisms behind learning, training effects and their predictors are not fully understood. Moreover, individual differences, which may constitute an important factor impacting training outcome, are usually neglected. We suggest investigating individual training performance across training sessions in order to gain finer-grained knowledge of training gains, on the one hand, and assessing the potential impact of predictors such as age and fluid intelligence on learning rate, on the other hand. To this aim, we propose to model individual learning curves to examine the intra-individual change in training as well as inter-individual differences in intra-individual change. We recommend introducing a latent growth curve model (LGCM) analysis, a method frequently applied to learning data but rarely used in cognitive training research. Such advanced analyses of the training phase allow identifying factors to be respected when designing effective tailor-made training interventions. To illustrate the proposed approach, a LGCM analysis using data of a 10-day working memory training study in younger and older adults is reported.
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“previous studies have already reported that at baseline, reasoning predicts training achievement (Bürki et al., 2014).”
From Training on Working Memory and Inhibitory Control in Young Adults (2016) · cites this paper as Bürki et al., 2014
In the citing paper
“In line with previously reported studies (Bürki et al., 2014), we have found that abstract reasoning was a meaningful predictor of training improvement, indicating that people with higher reasoning scores benefited more from training.”
From Training on Working Memory and Inhibitory Control in Young Adults (2016) · cites this paper as Bürki et al., 2014
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Self-citation
Metadata
- Authors
- Bürki, C. N., Ludwig, C., Chicherio, C., & de Ribaupierre, A.
- Affiliations
- University of Basel (CH)
- HES-SO Genève (CH)
- University Hospital of Geneva (CH)
- Corresponding author
- Bürki, Céline N.
- Venue
- Psychological Research
- Published
- 2014-03-21
- Volume
- 78
- Issue
- 6
- Pages
- 821-835
- ISSN
- 0033-3026 (ISSN-L)
- 0340-0727
- 1430-2772
- OpenAlex
- W1979135863
- Cited by
- 131
- References
- 111
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 4 · 2023: 8 · 2022: 12 · 2021: 15 · 2020: 24 · 2019: 15 · 2018: 9 · 2017: 17 · 2016: 7 · 2015: 5 · 2014: 4
- FWCI
- 15.30
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Psychological Research (publishedVersion)
- PubMed (publishedVersion)
- reroDoc Digital Library (submittedVersion)
- ArODES (HES-SO (https://www.hes-so.ch/)) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Functions and Memory
- Social Sciences › Psychology › Developmental and Educational Psychology › Aging and Gerontology Research
- Keywords
- cognitive training, individual differences, cognitive plasticity, learning curve, latent growth curve models, transfer of training, fluid intelligence, age differences, working memory training
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Aging, Cognition, Female, Humans, Individuality, Male, Memory, Short-Term, Middle Aged, Neuropsychological Tests, Transfer, Psychology, Young Adult, Learning Curve
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