Home-based CCT with adaptive difficulty and personal tailoring appears superior to more generic CCT in relation to both cognitive and non-cognitive outcomes. Mechanisms of treatment effect and future directions are discussed.

The growing prevalence of neurodegenerative disorders associated with aging and cognitive decline has generated increasing cross-disciplinary interest in non-pharmacological interventions, such as computerized cognitive training (CCT), which may prevent or slow cognitive decline. However, inconsistent findings across meta-analytic reviews in the field suggest a lack of cross-disciplinary consensus and on-going debate regarding the benefits of CCT. We posit that a contributing factor is the lack of a theoretically-based taxonomy of constructs and representative tasks typically used. An integration of the Cattell-Horn-Carroll (CHC) taxonomy of broad and narrow cognitive factors and the Miyake unity-diversity theory of executive functions (EF) is proposed (CHC-M) as an attempt to clarify this issue through representing and integrating the disciplines contributing to CCT research. The present study assessed the utility of this taxonomy by reanalyzing the Lampit et al. (2014) meta-analysis of CCT in healthy older adults using the CHC-M framework. Results suggest that: 1) substantively different statistical effects are observed when CHC-M is applied to the Lampit et al. meta-analytic review, leading to importantly different interpretations of the data; 2) typically-used classification practices conflate Executive Function (EF) tasks with fluid reasoning (Gf) and retrieval fluency (Gr), and Attention with sensory perception; and 3) there is theoretical and practical advantage in differentiating attention and working-memory tasks into the narrow shifting, inhibition, and updating EF domains. Implications for clinical practice, particularly for our understanding of EF are discussed.

The effects of repeated testing opportunities on score gains were investigated using scores from a sample of real estate licensee candidates (N=9,226). Score gains were significant, but minimal. In addition, responding to the same items on multiple occasions did not aid score gains, but length of time between retakes did.

The relationship between muscle fitness measures and tibial bone strength in collegiate level athletes was investigated. Eighty-six Division II collegiate athletes (age: (18-29 years), height: 1.71 m (.09): mass: 66.7 kg (10.5) 56 female: 30 male) participated in this cross-sectional study. Maximum grip strength (GS), 1 repetition maximum leg press (1RM) and vertical jump peak power (PP) tests were measured. Cortical area (Ct.Ar), cortical bone mineral density (cBMD), moment of inertia (J) and bone strength (polar strength-strain index, SSIp) were measured using peripheral quantitative computed tomography (pQCT) at 50% tibia length. For each bone strength parameter, a hierarchical multiple regression (HMR) analysis was performed to examine the contribution of sex and the 3 muscle fitness parameters (muscle power, relative 1 repetition leg extensor strength and relative grip strength) to bone parameters. Vertical jump peak power explained 54-59% of the variance in bone strength parameters, and relative leg extensor and grip strength were not predictive of bone strength parameters. Muscle power correlated with bone mass and architecture variables but not cBMD values. Cortical bone mineral density (cBMD) was also not predicted by relative leg extensor strength or relative grip strength. Muscular fitness assessment, specifically peak power calculated from vertical jump height assessments provides a simple, objective, valid and reliable measure to identify and monitor bone strength in collegiate athletes.