The Model Human Processor and the older adult: Parameter estimation and validation within a mobile phone task.
Open accessAbstract
The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; M-sub(age) = 20) and older (N = 20; M-sub(age) = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The processing-speed theory of adult age differences in cognition
Salthouse, T. A. (1996) · Psychological Review · doi:10.1037/0033-295x.103.3.403 · Cited by 5,568 · cited 3× · see citing works
“…including both cross-sectional studies and longitudinal studies, has investigated changes in cognitive function with aging, and findings reveal that working memory, information processing, selective attention, and problem-solving ability show differential decline with aging (e.g., Salthouse, 1996).”
BackgroundInfluentialCzaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006) · Psychology and Aging · doi:10.1037/0882-7974.21.2.333 · Cited by 2,113 · cited 8× · see citing works
“, (1983) 53 70 60–82 183 32 McFarland, Warren, & Karis (1958) 20 70 65–75 176 14 Nielsen-Bohlman & Knight (1999) 10 71 65–76 192 26 Picton, et al., (1984) 36 70 65–79 167 25 Picton, et al., (1986) 10 69 65–75 180 18 Podlesny & Dustman (1982) 16 71 65–75 180 30 Salthouse & Meinz (1995) 85 70 60–79 184 34 Sliwinski, et…”
BackgroundMethodInfluentialSelf-citationThe keystroke-level model for user performance time with interactive systems
Card, S. K., Moran, T. P., & Newell, A. (1980) · Communications of the ACM · doi:10.1145/358886.358895 · Cited by 1,174 · see citing works
Age-related performance of human subjects on saccadic eye movement tasks
Munoz, D. P., Broughton, J. R., Goldring, J. E., & Armstrong, I. T. (1998) · Experimental Brain Research · doi:10.1007/s002210050473 · Cited by 656 · see citing works
Aging and dual-task performance: A meta-analysis.
Verhaeghen, P., Steitz, D. W., Sliwinski, M. J., & Cerella, J. (2003) · Psychology and Aging · doi:10.1037/0882-7974.18.3.443 · Cited by 496 · see citing works
Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S., Erickson, K., & Becic, E. (2005) · Psychology and Aging · doi:10.1037/0882-7974.20.4.695 · Cited by 312 · see citing works
How older adults meet complexity: Aging effects on the usability of different mobile phones
Ziefle, M., & Bay, S. (2005) · Behaviour & Information Technology · doi:10.1080/0144929042000320009 · Cited by 194 · cited 3× · see citing works
“In the more complex text messaging task, the current study predicts that both human and model performance will be most time-efficient and least error-prone in menu navigation/text entry tasks using the mobile phone of least complex design (Ziefle, 2002; Ziefle & Bay, 2005).”
BackgroundMethodTouch a Screen or Turn a Knob: Choosing the Best Device for the Job
Rogers, W. A., Fisk, A. D., McLaughlin, A. C., & Pak, R. (2005) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/0018720054679452 · Cited by 141 · see citing works
Training Older Adults to Use Automatic Teller Machines
Rogers, W. A., Fisk, A. D., Mead, S. E., Walker, N., & Cabrera, E. F. (1996) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872096778701935 · Cited by 118 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Do “brain-training” programs work?
Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016) · Psychological Science in the Public Interest · doi:10.1177/1529100616661983 · Cited by 1,183 · see citing works
Self-citationAging and Information Technology Use: Potential and Barriers
Charness, N., & Boot, W. R. (2009) · Current Directions in Psychological Science · doi:10.1111/j.1467-8721.2009.01647.x · Cited by 674 · see citing works
Self-citationCharness, N. (2008) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872008x312161 · Cited by 247 · see citing works
Self-citationToward a Psychological Science of Advanced Technology Design for Older Adults
Rogers, W. A., & Fisk, A. D. (2010) · The Journals of Gerontology Series B: Psychological Sciences and Social Sciences · doi:10.1093/geronb/gbq065 · Cited by 204 · see citing works
Use and Design of Handheld Computers for Older Adults: A Review and Appraisal
Zhou, J., Rau, P.-L. P., & Salvendy, G. (2012) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2012.668129 · Cited by 118 · see citing works
Characteristics of Elderly User Behavior on Mobile Multi-touch Devices
Harada, S., Sato, D., Takagi, H., & Asakawa, C. (2013) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-40498-6_25 · Cited by 61 · see citing works
Interface adaptation to novice older adults’ mental models through concrete metaphors
Zhou, J., Chourasia, A., & Vanderheiden, G. (2017) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2016.1265827 · Cited by 32 · see citing works
- Authors
- Jastrzembski, T. S., & Charness, N.
- Affiliations
- Florida State University (US)
- ORCID
- Charness, Neil
- Venue
- Journal of Experimental Psychology: Applied
- Published
- 2007
- Volume
- 13
- Issue
- 4
- Pages
- 224-248
- ISSN
- 1076-898X (ISSN-L)
- 1939-2192
- PMC
- PMC4591021
- OpenAlex
- W2171626430
- Cited by
- 83
- References
- 9
- Citations by year
- 2026: 2 · 2025: 2 · 2023: 4 · 2022: 4 · 2021: 2 · 2020: 3 · 2019: 3 · 2018: 4 · 2017: 5 · 2016: 10 · 2015: 7 · 2014: 4 · 2013: 6 · 2012: 10
- FWCI
- 12.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Experimental Psychology Applied (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (1 PO1 AG17211-07)
- Topics
- Social Sciences › Demography › Technology Use by Older Adults
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Keywords
- older adults, mental workload, critical path method, age-related performance, parameter estimation, parameter validation
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Aging, Cognition, Female, Humans, Male, Mental Processes, Neuropsychological Tests, Reaction Time, Saccades, Cell Phone
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
