Characterizing Cognition in Everyday Life of Older Adults With Subjective Cognitive Decline

Rotenberg, Shlomit; Dawson, Deirdre

doi:10.1177/15394492221093310

Cited by 3 publications

(3 citation statements)

References 40 publications

(65 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Participation in social activities (item 13) involves the integration of executive functions with other complex cognitive processes that may be impacted by mild cognitive difficulties. 31 , 32 For example, subtle cognitive deficits can result in misinterpretations of social signals, context, emotions, behaviors, or verbal statements. 33 , 34 Organizing and managing finances (item 20) have been identified as being sensitive to mild cognitive impairment 35 , 36 because it requires the integration of different executive function skills.…”

Section: Discussionmentioning

confidence: 99%

Using machine learning to modify and enhance the daily living questionnaire

et al. 2023

View full text Add to dashboard Cite

The Daily Living Questionnaire (DLQ) constitutes one of a number of functional cognitive measures, commonly employed in a range of medical and rehabilitation settings. One of the drawbacks of the DLQ is its length which poses an obstacle to conducting efficient and widespread screening of the public and which incurs inaccuracies due to the length and fatigue of the subjects. Objective This study aims to use Machine Learning (ML) to modify and abridge the DLQ without compromising its fidelity and accuracy. Method Participants were interviewed in two separate research studies conducted in the United States of America and Israel, and one unified file was created for ML analysis. An ML-based Computerized Adaptive Testing (ML-CAT) algorithm was applied to the DLQ database to create an adaptive testing instrument—with a shortened test form adapted to individual test scores. Results The ML-CAT approach was shown to reduce the number of tests required on average by 25% per individual when predicting each of the seven DLQ output scores independently and reduce by over 50% when predicting all seven scores concurrently using a single model. These results maintained an accuracy of 95% (5% error) across subject scores. The study pinpoints which DLQ items are more informative in predicting DLQ scores. Conclusions Applying the ML-CAT model can thus serve to modify, refine and even abridge the current DLQ, thereby enabling wider community screening while also enhancing clinical and research utility.

show abstract

Section: Discussionmentioning

confidence: 99%

Using machine learning to modify and enhance the daily living questionnaire

et al. 2023

View full text Add to dashboard Cite

show abstract

“…This insight reinforces the importance of maintaining involvement in cognitive leisure activities, such as TECH at early stages. Improving occupational engagement, such as participating in cognitive leisure activities, may promote health and well-being of older adults with subjective cognitive decline, and may delay future cognitive and functional decline [ 4 ]. For example, older adults that participated leisure activities with high cognitive demands such as quilting and digital photography showed enhanced memory functions [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

“…Age-related cognitive decline (rather than physical decline) is also the biggest fear of older adults [ 3 ]. Therefore, many older adults are seeking ways to preserve their cognitive status and prevent future decline [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Daily Practice of Puzzle-Game Apps on Cognition in Two Groups of Older Adults: A Pre-Post Experimental Study

Schaham

Buckman

Rand

2022

IJERPH

View full text Add to dashboard Cite

There is an urgent need for non-pharmacological cognitive interventions to delay the onset and modify the progression of the cognitive deterioration of older adults with early stages of cognitive decline. ‘Tablet Enhancement of Cognition and Health’ (TECH) is such an intervention. We aimed to assess the suitability of TECH for older adults with and without mild cognitive impairment (MCI). Specifically, we wanted to explore the feasibility and to determine the initial effectiveness of TECH for older adults with Pre-Mild Cognitive Impairment (pre-MCI) as well as with MCI. This is pre-post experimental design, including two groups of older adults. Feasibility included group session attendance (adherence), self-training time (compliance), and satisfaction from the TECH intervention. The Montreal Cognitive Assessment (MoCA) assessed global cognition and the WebNeuro computerized battery assessed specific cognitive components. Twenty-eight participants with MCI (8 women, aged 65–87), and ten participants with pre-MCI (5 women, aged 65–86) participated in TECH. High adherence, compliance, and satisfaction were reported by both groups. Memory recall improved for the MCI group (z = −2.7 p = 0.006). In addition, for the MoCA an intermediate effect size (Cohen’s d = 0.52) and a small effect (Cohen’s d = 0.18) were found for the MCI and pre-MCI groups, respectively. Large to small effect size values for WebNeuro cognitive components were found for both groups. Both groups of older adults were motivated, performed daily self-training, which gave them enjoyment and a sense of control. TECH seems to have potential to preserve cognition over time. Additional research with a longer follow-up is needed to determine whether TECH can prevent cognitive decline in older adults with MCI but especially with pre-MCI.

show abstract