Digital Compensatory Cognitive Training for Older Adults with Memory Complaints

ABSTRACT

Many older people experience everyday memory complaints which can be a precursor condition to mild cognitive impairment and dementia. Research has consistently shown that compensatory cognitive training (CCT) benefits cognition in older adults. Providing CCT in a computerized format makes it more accessible and reduces its costs. We studied a newly developed digital CCT for older adults with everyday memory complaints that is multi-factorial and based on empirically supported techniques to improve memory. 55 older adults with self-reported everyday memory complaints participated in a study with outcomes assessed at baseline and post-intervention. We found that participants in the experimental condition improved significantly on the main objective outcome measure assessing associative memory compared to participants in a waitlist control condition. Specifically, after correcting for learning effects, 28% of participants in the experimental condition showed a reliable improvement. No effects were found on other objective outcome measures, most notably those assessing transfer to novel tasks. Participants in the experimental condition scored higher on measures of memory satisfaction, use of internal memory strategies, and quality of life. These findings contribute to existing knowledge on CCT by providing partial evidence for the efficacy of a digital CCT for older adults with everyday memory complaints. We recommend the use of digital CCT for older adults who experience memory complaints in their everyday life, but who do not qualify for medical treatment. Particular attention needs to be given to enhancing transfer of the learned strategies to everyday life.

KEYWORDS:

• Compensatory cognitive training
• everyday memory complaints
• memory strategy
• visual imagery

Acknowledgments

The authors wish to acknowledge the individuals who participated in this study. We would like to thank Dr. Björn Vlaskamp who has been one of the founders of the MemoryUp app. We furthermore would like to thank Dr. Ron Dotsch, Udhayakumar Samikannu, Mayur Agrawal, and Research Institutes Sweden who have all been involved in the software development of the MemoryUp app. The development of the MemoryUp app was supported by EIT Health and EIT Digital.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Sample size was determined with G*power based on expected small effect sizes (.2), with high test-retest effects (.7), a desired power of .8, and alpha of .005 (=0.5/10 since this study involved multiple testing with six objective and four subjective outcome measures). Power calculations indicated that 54 subjects were needed in total. 60 participants were recruited to compensate for early withdrawal, potential noncompliance or technical problems with the digital CCT.