Reliability and validity of a self-administered tool for online neuropsychological testing: The Amsterdam Cognition Scan

Introduction : To facilitate large-scale assessment of a variety of cognitive abilities in clinical studies, we developed a self-administered online neuropsychological test battery: the Amsterdam Cognition Scan (ACS). The current studies evaluate in a group of adult cancer patients: test–retest reliability of the ACS and the influence of test setting (home or hospital), and the relationship between our online and a traditional test battery (concurrent validity). Method : Test–retest reliability was studied in 96 cancer patients (57 female; Mage = 51.8 years) who completed the ACS twice. Intraclass correlation coefficients (ICCs) were used to assess consistency over time. The test setting was counterbalanced between home and hospital; influence on test performance was assessed by repeated measures analyses of variance. Concurrent validity was studied in 201 cancer patients (112 female; Mage = 53.5 years) who completed both the online and an equivalent traditional neuropsychological test battery. Spearman or Pearson correlations were used to assess consistency between online and traditional tests. Results : ICCs of the online tests ranged from .29 to .76, with an ICC of .78 for the ACS total score. These correlations are generally comparable with the test–retest correlations of the traditional tests as reported in the literature. Correlating online and traditional test scores, we observed medium to large concurrent validity (r/ρ = .42 to .70; total score r = .78), except for a visuospatial memory test (ρ = .36). Correlations were affected—as expected—by design differences between online tests and their offline counterparts. Conclusions : Although development and optimization of the ACS is an ongoing process, and reliability can be optimized for several tests, our results indicate that it is a highly usable tool to obtain (online) measures of various cognitive abilities. The ACS is expected to facilitate efficient gathering of data on cognitive functioning in the near future

Brain training improves recovery after stroke but waiting list improves equally: A multicenter randomized controlled trial of a computer-based cognitive flexibility training

Contains fulltext : 182441.pdf (publisher's version ) (Open Access)BACKGROUND: Brain training is currently widely used in an attempt to improve cognitive functioning. Computer-based training can be performed at home and could therefore be an effective add-on to available rehabilitation programs aimed at improving cognitive functioning. Several studies have reported cognitive improvements after computer training, but most lacked proper active and passive control conditions. OBJECTIVE: Our aim was to investigate whether computer-based cognitive flexibility training improves executive functioning after stroke. We also conducted within-group analyses similar to those used in previous studies, to assess inferences about transfer effects when comparisons to proper control groups are missing. METHODS: We conducted a randomized controlled, double blind trial. Adults (30-80 years old) who had suffered a stroke within the last 5 years were assigned to either an intervention group (n = 38), active control group (i.e., mock training; n = 35), or waiting list control group (n = 24). The intervention and mock training consisted of 58 half-hour sessions within a 12-week period. Cognitive functioning was assessed using several paper-and-pencil and computerized neuropsychological tasks before the training, immediately after training, and 4 weeks after training completion. RESULTS AND CONCLUSIONS: Both training groups improved on training tasks, and all groups improved on several transfer tasks (three executive functioning tasks, attention, reasoning, and psychomotor speed). Improvements remained 4 weeks after training completion. However, the amount of improvement in executive and general cognitive functioning in the intervention group was similar to that of both control groups (active control and waiting list). Therefore, this improvement was likely due to training-unspecific effects. Our results stress the importance to include both active and passive control conditions in the study design and analyses. Results from studies without proper control conditions should be interpreted with care

Healing with his hands

BACKGROUND: Stroke can result in cognitive complaints that can have a large impact on quality of life long after its occurrence. A number of computer-based training programs have been developed with the aim to improve cognitive functioning. Most studies investigating their efficacy used only objective outcome measures, whereas a reduction of subjective cognitive complaints may be equally important for improving quality of life. A few studies used subjective outcome measures but were inconclusive, partly due to methodological shortcomings such as lack of proper active and passive control groups. OBJECTIVE: The aim of the current study was to investigate whether computer-based cognitive flexibility training can improve subjective cognitive functioning and quality of life after stroke. METHODS: We performed a randomized controlled double blind trial (RCT). Adults (30-80 years old) who had a stroke 3 months to 5 years ago, were randomly assigned to either an intervention group (n = 38), an active control group (i.e., mock training; n = 35), or a waiting list control group (n = 24). The intervention and mock training consisted of 58 half-hour sessions within 12 weeks. The primary subjective outcome measures were cognitive functioning (Cognitive Failure Questionnaire), executive functioning (Dysexecutive Functioning Questionnaire), quality of life (Short Form Health Survey), instrumental activities of daily living (IADL; Lawton & Brody IADL scale), and participation in society (Utrecht Scale for Evaluation of Rehabilitation-Participation). Secondary subjective outcome measures were recovery after stroke, depressive symptoms (Hospital Anxiety Depression Scale-depression subscale), fatigue (Checklist Individual Strength-Fatigue subscale), and subjective cognitive improvement (exit list). Finally, a proxy of the participant rated the training effects in subjective cognitive functioning, subjective executive functioning, and IADL. RESULTS AND CONCLUSIONS: All groups improved on the two measures of subjective cognitive functioning and subjective executive functioning, but not on the other measures. These cognitive and executive improvements remained stable 4 weeks after training completion. However, the intervention group did not improve more than the two control groups. This suggests that improvement was due to training-unspecific effects. The proxies did not report any improvements. We, therefore, conclude that the computer-based cognitive flexibility training did not improve subjective cognitive functioning or quality of life after stroke