Effects of a computerized working memory training program on working memory, attention, and academics in adolescents with severe LD and comorbid ADHD: a randomized controlled trial

Abstract

Background: Youths with coexisting learning disabilities (LD) and attention deficit hyperactivity disorder (ADHD) are at risk for poor academic and social outcomes. The underlying cognitive deficits, such as poor working memory (WM), are not well targeted by current treatments for either LD or ADHD. Emerging evidence suggests that WM might be improved by intensive and adaptive computerized training, but it remains unclear whether this intervention would be effective for adolescents with severe LD and comorbid ADHD. Methods: A total of sixty 12-to 17-year olds with LD/ADHD (52 male, 8 female, IQ > 80) were randomized to one of two computerized intervention programs: working memory training (Cogmed RM) or math training (Academy of Math) and evaluated before and 3 weeks after completion. The criterion measures of WM included auditory-verbal and visual-spatial tasks. Near and far transfer measures included indices of cognitive and behavioral attention and academic achievement. Results: Adolescents in the WM training group showed greater improvements in a subset of WM criterion measures compared with those in the math-training group, but no training effects were observed on the near or far measures. Those who showed the most improvement on the WM training tasks at school were rated as less inattentive/hyperactive at home by parents. Conclusions: Results suggest that WM training may enhance some aspects of WM in youths with LD/ADHD, but further development of the training program is required to promote transfer effects to other domains of function.

Cognitive training as a resolution for early executive function difficulties in children with intellectual disabilities

“…The lack of far transfer effects suggest that WM training may only be reliable in producing changes in targeted domains and highlights the potential limits of this intervention in producing more widespread improvements. These findings are supported by additional investigations of far transfer effects as a result of WM training which have found no improvements in attention (Green et al, 2012;Thorell et al, 2009), ADHD symptoms (Green et al, 2012), response inhibition (Johnstone et al, 2011), IQ (Holmes et al, 2010) or academic achievement (Gray et al, 2012;Holmes, Gathercole, & Dunning, 2009). However an equal number of studies have found contradictory far transfer effects after WM training, with improvements being present in untrained domains such as attention (Beck et al, 2010;Goldin et al, 2013), ADHD symptoms (Johnstone et al, 2011;Klingberg et al, 2005;Mezzacappa & Buckner, 2010), response inhibition and reasoning (Klingberg et al, 2005;Klingberg et al, 2002).…”

“…For example, improving performance on verbal WM tasks after undergoing training on visuospatial WM tasks. These near transfer effects of WM training have been consistently reported using the CWMT program (Beck, Hanson, Puffenberger, Benninger, & Benninger, 2010;Gray et al, 2012;Green et al, 2012;Klingberg et al, 2005;Klingberg et al, 2002;Mezzacappa & Buckner, 2010;Thorell et al, 2009) as well as alternative working memory training programs; Jungle Memory (Alloway et al, 2013) and Mate Marote (Goldin et al, 2013).…”

“…The average amount of time for each session tends to be somewhere in the middle of these two extremes, at around 40 minutes (Beck et al, 2010;Gray et al, 2012;Klingberg et al, 2005;Klingberg et al, 2002;Mezzacappa & Buckner, 2010;Rueda et al, 2012;Rueda et al, 2005b). This poses significant difficulties when attempting to train processes such as attention.…”

What is the level of evidence for the use of currently available technologies in facilitating the self-management of difficulties associated with ADHD in children and young people? A systematic review

“…Reason for exclusion Barnett et al [86] Participants are teachers Benyakorn et al [87] Not interventional Bishop [88] Intervention not technology Bonarini et al [89] Population focus not ADHD Bul et al [90] Outcome measures do not assess ADHD-related difficulties Chan et al [91] Not interventional Chen et al [92] Not interventional Christiansen et al [93] Intervention reliant on others Dale and Grut [94] Not exclusively for ADHD Duffy [95] Population focus not ADHD Enebrink et al [96] Population focus not ADHD References Reason for exclusion Epstein et al [97] Intervention reliant on health care professionals Fiellin et al [98] Population focus not ADHD Frutos-Pascual et al [99] Population focus not ADHD Frutos-Pascual and GarciaZapirain [100] Participants typically developing, not ADHD Gray et al [72] ADHD not primary diagnosis of participants Halperin et al [101] Intervention not technology Janeslätt et al [102] Intervention not technology Kim et al [103] Intervention not technology Lim et al [104] Intervention reliant on health care professionals Mazurek and Engelhardt [105] Not interventional Myers et al [106] Participants ADHD diagnosis not confirmed Nie et al [107] Intervention not technology Pandria et al [108] Not interventional Rohani et al [109] Participants ADHD diagnosis not confirmed Rosch and Mostofsky [110] Not interventional Schafer et al [111] Participants not received ADHD diagnosis Schuck et al [112] Participants not received ADHD diagnosis Shah et al 2012 Not interventional Silva et al [113] Technology as outcome measure, not intervention Steeger et al 2016 Participants ADHD diagnosis not confirmed Stephenson [114] Population focus not ADHD Tse et al …”

LearningRx Cognitive Training Effects in Children Ages 8–14: A Randomized Controlled Trial

“…Given the growing research base on the associations among working memory and intelligence (Cornoldi & Giofre, 2014), and working memory and learning (Alloway & Copello, 2013), it is easy to see why a majority of the cognitive training programs target working memory. Certainly, most of the studies do cite improvements in working memory (Beck, Hanson, & Puffenberger, 2010; Dunning et al, 2013; Gray et al, 2012; Holmes & Gathercole, 2014; Wiest, Wong, Minero, & Pumaccahua, 2014), but pretest to post‐test gains have also been documented in fluid reasoning (Barkl, Porter, & Ginns, 2012; Jaeggi et al, 2008; Mackey, Hill, Stone, & Bunge, 2011), processing speed (Mackey et al, 2011), reading (Loosli, Buschkuehl, Perrig, & Jaeggi, 2012; Shalev, Tsal, & Mevorach, 2007), computational accuracy (Witt, 2011), and attention (Rabiner, Murray, Skinner, & Malone, 2010; Tamm, Epstein, Peugh, Nakonezny, & Hughes, 2013). …”