Does Working Memory Impact Functional Outcomes in Individuals With ADHD: A Qualitative and Comprehensive Literature Review

Abstract

Objective: Working Memory (WM) is a domain of executive functioning often impaired in individuals with ADHD. Although assumed to cause difficulties across functioning, the scope of impairments from WM deficits in ADHD has not been investigated. The aim of this study was to examine outcomes associated with WM deficits in ADHD. Method: We conducted a search of the scientific literature on WM deficits, and Freedom From Distractibility (FFD), in ADHD using PubMed and PsycInfo databases. Results: The final sample included 11 controlled studies of WM/FFD deficits in ADHD with operationalized assessment of outcomes in academic, social, and emotional areas. WM assessment was divided into auditory-verbal memory (AVM) and spatial-visual memory (SWM). Seven studies examined WM deficits in academic functioning, eight studies assessed WM deficits in social functioning, and three assessed WM deficits in psychopathology. Conclusion: The majority of the literature suggests that WM deficits affect primarily academic functioning.

Keywords

ADHD working memory Freedom From Distractibility functional impairment academic impairment social impairment

Introduction

ADHD is a highly prevalent morbid disorder estimated to affect up to 11% of children (Centers for Disease Control and Prevention, 2016). One source of impairment in ADHD is deficits in executive functions (EFDs; Barkley & Murphy, 2010; Biederman et al., 2006; Biederman et al., 2007; Faraone et al., 2006), a group of high-order cognitive functions necessary for goal-directed activities, of which working memory is a prominent component. Working Memory (WM) as well as its predecessor, Freedom From Distractibility (FFD), refers to the ability to hold information in mind for use in complex tasks (Alderson, Kasper, Hudec, & Patros, 2013; Baddeley, 1998). WM deficits are often thought to be core symptoms of ADHD; however, they are not present in all individuals with ADHD and need specialized assessment to be diagnosed. While ADHD is diagnosed with clinical interviews and checklists that rely on behavioral observations, WM deficits can only be assessed through psychometric testing.

Because of its importance in learning and everyday tasks, WM deficits can be expected to have a wide range of adverse functional consequences when impaired (Alloway & Alloway, 2010). Yet the scope of the adverse outcomes of these deficits within ADHD has not been adequately investigated. A better understanding of the impact of WM deficits in ADHD has important implications. Insights about the morbidity of WM deficits and ADHD will first encourage clinicians managing children with ADHD to assess WM deficits with psychometric testing. Such information can help further define a homogeneous subgroup of ADHD patients with unique neurobiological underpinnings and identify more specific presentations of the disorder. Moreover, because pharmacological treatments for ADHD have limited impact on WM (Biederman et al., 2008; Matsuura et al., 2014), identification of WM deficits within ADHD will hopefully lead to appropriate targeted interventions (Arnsten, 2009; Biederman et al., 2008; Faraone, 2012; Pietrzak, Mollica, Maruff, & Snyder, 2006; Swanson, Baler, & Volkow, 2011).

The main aim of this study was to examine the available literature on WM deficits in ADHD to assess the scope of outcomes associated with it. We conducted a systematic literature search of scientific articles on ADHD and WM deficits. We hypothesized that WM deficits in ADHD will be associated with a wide range of functional deficits.

Method

We conducted a comprehensive search of the scientific literature on WM deficits, and its predecessor FFD, in ADHD relying on PubMed and PsycInfo databases. We used the following search criteria: (ADHD [All Fields] AND Working Memory deficits [All Fields] as well as ADHD [All Fields] AND Freedom From Distractibility [All Fields]). To be included in our review, we restricted the literature to studies that met the following criteria: (a) operationalized diagnosis of ADHD, (b) psychometric assessment of WM, (c) utilization of healthy controls, and (d) operationalized assessment of functional outcomes.

Data Extraction

The following variables were extracted: (a) numbers of participants in ADHD and control groups, (b) age group (pediatric, adolescent, adult), (c) tests and domain (auditory-verbal [AVM] or spatial-visual [SWM]) used in the assessment of WM, (d) specific measures of functional outcomes, and (e) type of study design (longitudinal or cross-sectional).

Results

As shown in Figure 1, the initial search in PubMed and PsycInfo identified 1,188 manuscripts with (a) ADHD, (b) either WM (1,144) or its predecessor FFD (44), (c) Functional Outcomes [All Fields] OR Academic* [All Fields] OR Social* [All Fields], (d) articles written in the English language, (e) peer-reviewed, (f) not a review article, and (g) controlled studies. The significant correlation of .72 between the Freedom of Distractibility Factor and the Working Memory Index of the Wechsler Intelligence Scale for Children–IV (WISC-IV) renders the use of FFD factor scores an appropriate proxy for WM index (Wechsler, 2003).

Figure 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.

The search criteria reduced the number of manuscripts to 105. Of these, 94 articles were removed due to the absence of an operationalized diagnosis of ADHD and/or lack of formal assessment of WM, a control group, or operationalized assessment of functional outcomes. The final sample used in this review was 11 articles that met our inclusion and exclusion criteria. Within the 11 articles, effects of WM deficits were assessed in three functional domains: academic, social, and emotional. Three articles examined academic functioning only and three examined social functioning only. Two articles examined social and academic problems and one assessed social and emotional problems. Two articles looked at all three domains: academic, social and emotional. Of these 11 articles, only two assessed adult participants. Otherwise, the articles were limited to pediatric samples.

Assessment of WM

The assessment of WM was divided into two domains: auditory-verbal memory (AVM), which refers to the manipulation of read or heard information involving language, and spatial-visual memory (SWM), which refers to the manipulation of visual item locations or the relationship between visual items. Of the 11 studies identified, seven tested both AVM and SWM, two tested AVM only, and two tested SWM only. In regard to the range of methods to measure WM, eight studies used the Wechsler Working Memory Index (FFD) scales to assess AVM. Of these, two studies used the Wechsler measures exclusively, five used the Wechsler scales with customized research measures, and one used the Wechsler scales with customized research measures and a subtest of the Cambridge Neuropsychological Test Automated Battery (CANTAB; to measure SWM with a computerized test). One study used only customized research measures of both AVM and SWM, and two studies used only the CANTAB to measure SWM (Table 1).

Table 1.

Studies Included in Qualitative and Comprehensive Review.

Authors	Age range (years)	n	Referred versus nonreferred	Scope	Study design	Domain	Types of measures	Findings
Gropper and Tannock (2009)	19-34	16 ADHD 30 controls	Nonreferred	Determine whether WM is related to academic functioning	Cross-sectional	AVM SWM	Wechsler, CANTAB, and Custom	Significant relationship between GPA and auditory-verbal WM
Alloway, Elliott, and Place (2010)	9	13 inattentive sx 13 ADHD-C 13 low WM 13 controls	Nonreferred	Examine WM profiles for ADHD subtypes, relationship between WM and academic attainment, and differences in WM profiles for inattentive students versus those with poor WM	Cross-sectional	AVM SWM	Wechsler and Custom	Combined and inattentive subtypes could not be distinguished on the basis of their WM profile. The majority of all three atypical groups performed very poorly in reading and math.
Kofler et al. (2011)	8-12	23 ADHD 16 typically developing	Referred	Impact of WM deficits on parent- and teacher-reported social problems	Cross-sectional	AVM SWM	Custom	Central executive WM processes contribute to children’s inattentive and hyperactive/impulsive behavior—and in doing so, negatively impact their social interactions.
Rinsky and Hinshaw (2011)	6–12 Followed over 5 years	140 ADHD 88 controls	Referred	Impact of childhood levels of EF on adolescent social functioning and psychopathology	Longitudinal	AVM	Wechsler	Marginally significant effect of childhood WM on adolescent social functioning and the presence of an adolescent internalizing disorder.
Miller, Nevado-Montenegro, and Hinshaw (2012)	6-12 Tested again at 11-17 and 17-23	140 ADHD 88 controls	Mixed	The ability of childhood measures of EF to predict academic, socioemotional, occupational, and psychopathological outcomes at follow-up.	Longitudinal	AVM SWM	Wechsler and Custom	Childhood WM predicted academic and occupational functioning across entire sample, but diagnostic status moderated the association between WM and reading achievement (in the ADHD group, low WM predicted poor reading scores)
Tseng and Gau (2013)	11-17	279 ADHD: divided into two identified subgroups: social problems (n = 70) and without social problems (n = 31) 173 controls	Referred	The extent to which EF mediates the association between ADHD and social problems. Also, to examine differences among ADHD youth with and without social problems on severity of ADHD, psychiatric comorbidities, and EF.	Cross-sectional	SWM	CANTAB	WM mediated the effect of ADHD on social problems. The two ADHD groups with and without social problems did not differ in ADHD severity or comorbidities; however, ADHD youth without social problems performed better on WM.
Rennie, Beebe-Frankenberger, and Swanson (2014)	Time 1: 6-9 Time 2: 8-11	17 high ADHD sx 34 low ADHD sx	Nonreferred	Determine relationship between ADHD and academic performance by looking at cognitive variables and academic achievement	Longitudinal	AVM SWM	Wechsler and Custom	Analysis revealed that for the high ADHD symptom group, WM served as an important moderator between ADHD signs and math performance.
Bunford et al. (2015)	8-12	34 ADHD 30 non-ADHD	Mixed	Relationship between executive deficits, ADHD symptoms, and social impairment	Cross-sectional	AVM SWM	Wechsler and Custom	ADHD sxs mediate the effects of nonverbal WM on social impairment.
Sjowall and Thorell (2014)	7-13	102 ADHD 102 controls	Referred	The extent to which EF deficits, delay aversion, RT variability, and emotional functioning function as mediators in the relation between ADHD and academic achievement and peer problems	Cross-sectional	AVM SWM	Wechsler and Custom	Deficits in WM and RT variability mediated the relation between ADHD and academic achievement, and regulation of anger mediated the relationship between ADHD and peer problems. Deficiency in WM was significantly related to academic achievement (language scales and mathematics) but not to peer problems when controlling for ADHD status.
Chiang and Gau (2014)	8-18	124 controls without EF deficits 121 ADHD with SWM and SOC deficits 185 ADHD with SWM or SOC deficits 205 ADHD without SWM or SOC deficits	Nonreferred	The role of key executive functions (EF, i.e., SWM and spatial planning) on school and peer functions	Cross-sectional	SWM	CANTAB	ADHD dx shows significant adverse effect on the relationship of all school and peer functions. Deficit in SWM was significantly associated with more severe problems in school and peer functions.
Fried et al. (2016)	6-18	276 ADHD 241 controls	Referred	Determine whether educational and social deficits are driven by WM deficits or ADHD. Also to assess the effect of WM deficits on psychopathology.	Cross-sectional	AVM	Wechsler	Significantly more youth with ADHD had WM deficits than controls. In children with ADHD, WM deficits were significantly associated with an increased risk for grade retention and placement in special classes as well as lower scores on reading and math achievement tests than for children with ADHD without WM deficits. No other differences were noted in other areas of functioning.

Note. WM = working memory; AVM = auditory-verbal memory; SWM = spatial-visual memory; CANTAB = Cambridge Neuropsychological Test Automated Battery; GPA = grade point average; EF = executive function; RT= rate; SOC= Stockings of Cambridge.

Impact of WM Deficits on Academic Functioning

Of the seven studies that examined the impact of WM deficits on academic functioning, all found deficits in this area. Three studies found WM deficits had a significant adverse impact on reading and math scores. (Alloway, Elliott, & Place, 2010; Miller, Nevado-Montenegro, & Hinshaw, 2012; Rennie, Beebe-Frankenberger, & Swanson, 2014; Table 1). In addition, four articles reported on the adverse outcome of WM deficits on academic achievement or performance (Chiang & Gau, 2014; Fried et al., 2016; Gropper & Tannock, 2009; Sjowall & Thorell, 2014). Gropper and Tannock (2009) found that AVM had a significant adverse impact in academic performance as reflected in poor grade point average (GPA). Other related academic findings include Chiang and Gau’s (2014) finding that SWM deficits were associated with behavioral problems in school as measured by the Social Adjustment Inventory for Children and Adolescents (SAICA). In addition, Fried et al. found that AVM deficits were significantly associated with academic deficits as measured by grade retention and placement in special classes (Table 1).

Impact of WM Deficits on Social Functioning

Eight articles examined the effects of WM deficits on social functioning (Bunford et al., 2015; Chiang & Gau, 2014; Fried et al., 2016; Kofler et al., 2011; Miller et al., 2012; Rinsky & Hinshaw, 2011; Sjowall & Thorell, 2014; Tseng & Gau, 2013). Kofler et al. (2011), Tseng and Gau (2013), and Bunford et al. (2015) found that SWM deficits contributed to social impairment in youth with ADHD (e.g., being teased, less liked, and not getting along with peers). Chiang and Gau (2014) reported that SWM deficits were also associated with deficits in social interaction in school, school behavior problems, peer social interaction, and peer problems. Rinsky and Hinshaw (2011) found a detrimental effect of WM on adolescent social functioning. In contrast, Miller et al. (2012), Sjowall and Thorell (2014), and Fried et al. (2016) did not find any significant correlations between WM deficits and social functioning (Table 1).

Impact of WM Deficits on Psychopathology

Three articles examined the effects of WM deficits on psychopathology. Rinsky and Hinshaw (2011) found a marginally significant effect of childhood WM deficits on adolescent internalizing disorders. In contrast, Fried et al.(2016) did not find meaningful associations between WM deficits and psychiatric disorders. Finally, in Miller et al. (2012) WM predicted nonsuicidal self-injury (NSSI)/suicide attempts, but this finding was no longer significant when they controlled for group status (ADHD vs. control).

Conclusion

This literature search identified 11 controlled studies that examined the effect of WM deficits on functioning in individuals with ADHD. Despite the wide variety of tests used to assess WM, the two aspects of WM (AVM/SWM) and the various outcome measures assessed, the majority of the available literature suggests that WM deficits affect primarily academic functioning.

This robust finding of the effect of WM deficits on academic functioning was present in all seven of the studies that assessed this area. This finding was present regardless of the tests used to document WM deficits, the type of WM deficit (AVM or SWM), and the outcome measured (scores on math tests, reading tests, GPA, grades). This finding is not surprising considering the well-documented association between WM and the skills necessary for successful learning (Alloway & Alloway, 2010; Archibald, Joanisse, & Edmunds, 2011). Laboratory tasks designed to simulate the high WM demands of classroom activities confirm the critical importance of WM for learning (Engle, Carullo, & Collins, 1991; Gathercole, Durling, Evans, Jeffcock, & Stone, 2008).

Considering the high prevalence of ADHD, its documented impact on academic functioning, and its high overlap with WM deficits, the detrimental effects of WM deficits in ADHD on academic functioning has very high clinical, educational, and public health relevance. In a recent study, it was documented that ADHD is a significant risk factor for grade retention and dropping out of school, adjusting for social class and IQ (Fried et al., 2013). Every year in the United States, about 1.2 million students fail to graduate from high school on time (Editorial Projects in Education, 2011). Doll, Eslami, and Walters (2013) found that poor grades were the cause for approximately 38% of early termination from high school. Failing to graduate from high school has been shown to have severe adverse life-course consequences for these individuals such as poorer health and greater demand on social welfare (Freudenberg & Ruglis, 2007), lower standard of living, and impaired social mobility (Kessler, Foster, Saunders, & Stang, 1995). Moreover, failure to graduate from high school leads to lower wages, shorter lives (Muennig, 2005), and higher likelihood to commit crimes (Muennig, 2005; Raphael, 2004). Also, adding to this problem, WM has been shown to be a factor in grade retention (Fried et al., 2016), which is correlated with students being 4 times as likely not to complete high school or to receive a Graduate Equivalent Degree (GED).

The results of the eight studies that assessed social problems were more equivocal. Because social functioning and WM deficits in these studies were assessed by disparate measures, interpretation of these finding is difficult. The mechanism by which WM deficits are causal in reducing academic success has been well documented; however, the effect on social behaviors in less clear. There is a small literature that documents that students who underperform in school may be less socially accepted than their classmates (McKown, Gumbiner, & Johnson, 2011; Mrug et al., 2012). Therefore, there is a question as to whether deficits in WM directly contribute to poorer social behaviors and peer rejection or whether children’s rejection is due to poor performance in school, as a result of WM deficits. In addition, peer rejection in these scenarios may further hinder the development of positive social behavior, creating a difficult-to-break cycle. Since many of the studies that assessed social functioning also reported academic deficits, it could be that the social problems are secondary to academic deficits such as being less adept in school. More work is needed to further examine this issue.

The lack of robust findings in the literature regarding psychopathology is an interesting and somewhat unexpected finding. However, it must be considered in light of the fact that the majority of participants had not yet fully matured past the age of risk for many psychiatric disorders that could be linked to WM deficits.

Our findings need to be viewed in light of some methodological limitations. First, the available literature was small and almost exclusively focused on youth. The methods of measuring WM were inconsistent. In addition, methods of measuring outcomes were similarly inconsistent. Measures of social problems ranged from parent to teacher to self-report. Measures of academic outcomes ranged from performance on reading and math to self-reported GPA to parent-reported grades.

Despite these limitations, our review of the literature documents that WM deficits affect primarily educational functioning. Given the high morbidity and disability associated with academic dysfunction, more efforts are needed to help identify WM deficits in individuals with ADHD. More research is needed to help characterize the impact of WM deficits in adults with ADHD and develop appropriate interventions to help address them.

Footnotes

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: J.B. is currently receiving research support from the following sources: American Academy of Child and Adolescent Psychiatry (AACAP), The Department of Defense, Food & Drug Administration, Headspace, Lundbeck, Neurocentria Inc., National Institute on Drug Abuse (NIDA), PamLab, Pfizer, Shire Pharmaceuticals Inc., Sunovion, and National Institutes of Health (NIH). He has a financial interest in Avekshan LLC, a company that develops treatments for ADHD. His interests were reviewed and are managed by Massachusetts General Hospital (MGH) and Partners HealthCare in accordance with their conflict of interest policies. His program has received departmental royalties from a copyrighted rating scale used for ADHD diagnoses, paid by Ingenix, Prophase, Shire, Bracket Global, Sunovion, and Theravance; these royalties were paid to the Department of Psychiatry at MGH. In 2017, J.B. is a consultant for Aevi Genomics, Akili, Guidepoint, Medgenics, and Piper Jaffray. He is on the scientific advisory board for Alcobra and Shire. He received honoraria from the MGH Psychiatry Academy for tuition-funded Continuing Medical Education (CME) courses. Through MGH corporate licensing, he has a U.S. Patent (#14/027,676) for a nonstimulant treatment for ADHD and a patent pending (#61/233,686) on a method to prevent stimulant abuse. R.F., J.A., A.H., L.F., and A.P. have no conflicting interests to report.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by the MGH Pediatric Psychopharmacology Council Fund. The funding sources had no role in the study design; in the collection, analysis, or interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Author Biographies

Ronna Fried, EdD, is the director of neuropsychology in the Clinical and Research Program in Pediatric Psychiatry and Adult ADHD in the Department of Psychiatry at Massachusetts General Hospital. Her research focuses on understanding the neuropsychological profiles of individuals across the life span with ADHD, pediatric bipolar disorder, and autism spectrum disorders.

Jessica Abrams, BA, is a research assistant in the Clinical and Research Program in Pediatric Psychopharmacology and Adult ADHD. She has a bachelor’s degree and provides research support to the principal investigators in the department.

Anna Hall, BA, is a research assistant in the Clinical and Research Program in Pediatric Psychopharmacology and Adult ADHD. She has a bachelor’s degree and provides research support to the principal investigators in the department.

Leah Feinberg, BA, is a research assistant in the Clinical and Research Program in Pediatric Psychopharmacology and Adult ADHD. She has a bachelor’s degree and provides research support to the principal investigators in the department.

Amanda Pope, BS, is a research assistant in the Clinical and Research Program in Pediatric Psychopharmacology and Adult ADHD. She has a bachelor’s degree and provides research support to the principal investigators in the department.

Joseph Biederman, MD, is chief of the Clinical and Research Program in Pediatric Psychopharmacology and Adult ADHD at the Massachusetts General Hospital, director of the Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorders at the Massachusetts General Hospital, and professor of Psychiatry at the Harvard Medical School. Also, he is Board Certified in General and Child Psychiatry.

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