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Early prediction of mastery of a computerized functional skills training program in participants with mild cognitive impairment

Published online by Cambridge University Press:  21 February 2024

Philip D. Harvey Open the ORCID record for Philip D. Harvey [Opens in a new window] ,
Courtney Dowell-Esquivel ,
Justin E. Macchiarelli ,
Alejandro Martinez ,
Peter Kallestrup  and
Sara J. Czaja
Philip D. Harvey*
Affiliation:
University of Miami Miller School of Medicine, Miami, FL, USA I-Function, Inc, Miami, FL, USA
Courtney Dowell-Esquivel
Affiliation:
University of Miami Miller School of Medicine, Miami, FL, USA
Justin E. Macchiarelli
Affiliation:
University of Miami, Coral Gables, FL, USA
Alejandro Martinez
Affiliation:
University of Miami Miller School of Medicine, Miami, FL, USA
Peter Kallestrup
Affiliation:
I-Function, Inc, Miami, FL, USA
Sara J. Czaja
Affiliation:
I-Function, Inc, Miami, FL, USA Weill-Cornell Medical Center, New York, NY, USA
*
Correspondence should be addressed to: P. D. Harvey, Department of Psychiatry and Behavioral Sciences, University of Miami, Miller School of Medicine, 1120 NW14th Street, Suite 1450, Miami, FL 33136, USA. E-mail: pharvey@miami.edu
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Abstract

Background:

Cognition in MCI has responded poorly to pharmacological interventions, leading to use of computerized training. Combining computerized cognitive training (CCT) and functional skills training software (FUNSAT) produced improvements in 6 functional skills in MCI, with effect sizes >0.75. However, 4% of HC and 35% of MCI participants failed to master all 6 tasks. We address early identification of characteristics that identify participants who do not graduate, to improve later interventions.

Methods:

NC participants (n = 72) received FUNSAT and MCI (n = 92) participants received FUNSAT alone or combined FUNSAT and CCT on a fully remote basis. Participants trained twice a week for up to 12 weeks. Participants “graduated” each task when they made one or fewer errors on all 3–6 subtasks per task. Tasks were no longer trained after graduation.

Results:

Between-group comparisons of graduation status on baseline completion time and errors found that failure to graduate was associated with more baseline errors on all tasks but no longer completion times. A discriminant analysis found that errors on the first task (Ticket purchase) uniquely separated the groups, F = 41.40, p < .001, correctly classifying 94% of graduators. An ROC analysis found an AUC of .83. MOCA scores did not increase classification accuracy.

Conclusions:

More baseline errors, but not completion times, predicted failure to master all FUNSAT tasks. Accuracy of identification of eventual mastery was exceptional. Detection of risk to fail to master training tasks is possible in the first 15 minutes of the baseline assessment. This information can guide future enhancements of computerized training.

Keywords

activities of daily livingcognitive trainingmild cognitive impairment
Type
Original Research Article
Information
International Psychogeriatrics , First View , pp. 1 - 12
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Psychogeriatric Association

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