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Long-term effects of cognitive training on everyday functional outcomes in older adults

TLDR
Cognitive training resulted in improved cognitive abilities specific to the abilities trained that continued 5 years after the initiation of the intervention, and booster training for the speed of processing group showed a significant effect on the performance-based functional measure of everyday speed ofprocessing.
Abstract
ContextCognitive training has been shown to improve cognitive abilities in older adults but the effects of cognitive training on everyday function have not been demonstrated.ObjectiveTo determine the effects of cognitive training on daily function and durability of training on cognitive abilities.Design, Setting, and ParticipantsFive-year follow-up of a randomized controlled single-blind trial with 4 treatment groups. A volunteer sample of 2832 persons (mean age, 73.6 years; 26% black), living independently in 6 US cities, was recruited from senior housing, community centers, and hospitals and clinics. The study was conducted between April 1998 and December 2004. Five-year follow-up was completed in 67% of the sample.InterventionsTen-session training for memory (verbal episodic memory), reasoning (inductive reasoning), or speed of processing (visual search and identification); 4-session booster training at 11 and 35 months after training in a random sample of those who completed training.Main Outcome MeasuresSelf-reported and performance-based measures of daily function and cognitive abilities.ResultsThe reasoning group reported significantly less difficulty in the instrumental activities of daily living (IADL) than the control group (effect size, 0.29; 99% confidence interval [CI], 0.03-0.55). Neither speed of processing training (effect size, 0.26; 99% CI, −0.002 to 0.51) nor memory training (effect size, 0.20; 99% CI, −0.06 to 0.46) had a significant effect on IADL. The booster training for the speed of processing group, but not for the other 2 groups, showed a significant effect on the performance-based functional measure of everyday speed of processing (effect size, 0.30; 99% CI, 0.08-0.52). No booster effects were seen for any of the groups for everyday problem-solving or self-reported difficulty in IADL. Each intervention maintained effects on its specific targeted cognitive ability through 5 years (memory: effect size, 0.23 [99% CI, 0.11-0.35]; reasoning: effect size, 0.26 [99% CI, 0.17-0.35]; speed of processing: effect size, 0.76 [99% CI, 0.62-0.90]). Booster training produced additional improvement with the reasoning intervention for reasoning performance (effect size, 0.28; 99% CI, 0.12-0.43) and the speed of processing intervention for speed of processing performance (effect size, 0.85; 99% CI, 0.61-1.09).ConclusionsReasoning training resulted in less functional decline in self-reported IADL. Compared with the control group, cognitive training resulted in improved cognitive abilities specific to the abilities trained that continued 5 years after the initiation of the intervention.Trial Registrationclinicaltrials.gov Identifier: NCT00298558

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Statistical Power Analysis for the Behavioral Sciences

TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
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“Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician

TL;DR: A simplified, scored form of the cognitive mental status examination, the “Mini-Mental State” (MMS) which includes eleven questions, requires only 5-10 min to administer, and is therefore practical to use serially and routinely.

A practical method for grading the cognitive state of patients for the clinician

TL;DR: The Mini-Mental State (MMS) as mentioned in this paper is a simplified version of the standard WAIS with eleven questions and requires only 5-10 min to administer, and is therefore practical to use serially and routinely.
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Analysis of Incomplete Multivariate Data

TL;DR: The Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data and Inference by Data Augmentation Methods for Normal Data provide insights into the construction of categorical and mixed data models.
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Nonparametrics: Statistical Methods Based on Ranks

TL;DR: Rank Tests for Comparing Two Treatments and Blocked Comparisons for two Treatments in a Population Model and the One-Sample Problem as discussed by the authors were used to compare more than two treatments.
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