Inattention Symptoms Are Associated With Academic Achievement Mostly Through Variance Shared With Intrinsic Motivation and Behavioral Engagement

Abstract

Objective: The main goal of the current study is to investigate whether intrinsic motivation and behavioral engagement mediate the association between inattention symptoms and academic achievement (reading, writing, and mathematics), as well as to document the extent to which inattention symptoms contribute to academic achievement due to variance overlapping with intrinsic motivation and behavioral engagement. Method: Participants were 92 children (Grades 1-4). Data were gathered using a combination of parent and teacher reports as well as objective assessments. Results: Results did not support the mediating role of intrinsic motivation and behavioral engagement. A commonality analysis showed that 77.44% to 82.10% of the variance explained in each academic achievement domains was due to variance shared by inattention symptoms, intrinsic motivation, and behavioral engagement. Conclusion: These results suggest more commonality than differences between inattention symptoms, intrinsic motivation, and behavioral engagement with regard to their association with academic achievement. The implications of these findings are discussed.

Keywords

academic performance classroom impairment inattention

Introduction

ADHD, characterized by symptoms of inattention and hyperactivity/impulsivity, is often associated with significant levels of impairment in school, including academic underachievement and grade failure (Bauermeister et al., 2007; Lahey et al., 2004). Evidence indicates that the academic impairments related to ADHD are related primarily to inattention symptoms, which are predictive of academic underachievement in community samples of children (Duncan et al., 2007) as well as clinical samples of children diagnosed with ADHD (Lahey & Willcutt, 2010). Furthermore, inattention symptoms are related to academic difficulties in a broad set of academic domains including reading (Dally, 2006; Martinussen, Grimbos, & Ferrari, 2014; Willcutt et al., 2010), mathematics (Martin et al., 2013), and composition fluency and accuracy (Kim, Al Otaiba, Sidler, & Gruelich, 2013). Importantly, the association between inattention symptoms and academic underachievement is not explained by co-occurring behaviors such as hyperactivity/impulsivity, conduct problems, and anxiety (Duncan et al., 2007; Polderman, Boomsma, Bartels, Verhulst, & Huizink, 2010). Given the ability of inattention symptoms measured close to school entry to predict later academic achievement (Duncan et al., 2007), a clear understanding of the mechanisms accounting for their contribution to academic outcomes may have important implications for the prevention of academic underachievement.

Theoretical models posit that the link between inattentive behavior and academic underachievement is mediated by intermediary factors (Demaray & Jenkins, 2011; Rapport, Scanlan, & Denney, 1999; Volpe et al., 2006). To date, considerable emphasis has been placed on the role of cognitive difficulties (e.g., processing speed, executive functions) as potential mediators of the association between ADHD symptoms and academic achievement (Biederman et al., 2004; Langberg, Dvorsky, & Evans, 2013; Miller & Hinshaw, 2010). In the current study, we investigate the roles of two additional factors that have been hypothesized to account for the association between inattention symptoms and academic achievement: intrinsic motivation and behavioral engagement (Volpe et al., 2006). Intrinsic motivation and behavioral engagement are useful to explore given their importance to academic achievement (Spinath, Spinath, Harlaar, & Plomin, 2006; Wang & Eccles, 2012; Yeung & McInerney, 2005) and their documented relationship with ADHD symptoms or status (Volpe et al., 2006) as well as executive functions (EF; Sasser, Bierman, & Heinrichs, 2015). The first goal of our study, therefore, is to investigate whether behavioral inattention is indirectly associated with academic achievement measures via intrinsic motivation and behavior engagement. Our second goal is to examine the extent to which academic achievement domains are predicted by variance shared between the constructs under consideration (inattention, intrinsic motivation, and behavioral engagement) or unique to each construct. This latter question is important to address as is important to understand whether we should focus on understanding the commonalities or specificities of these constructs to better predict academic achievement.

There is substantial evidence of a relationship between academic motivation and academic outcomes in children and adolescents (Hattie, 2013; Steinmayr & Spinath, 2009). Although there are various motivation constructs relevant to academic success, here we focus on intrinsic motivation, that is, the tendency for an individual to do something because it is inherently interesting, enjoyable, or challenging (Fortier, Vallerand, & Guay, 1995; Ryan & Deci, 2000). Students who are intrinsically motivated tend to seek challenge, persist on difficult tasks, and strive to improve their own performance rather than to rely on the presence of external rewards (Green et al., 2012; Walker, Greene, & Mansell, 2006). It is hypothesized that intrinsic motivation results in positive behaviors, cognitions, and thoughts in the school context that are associated with academic success (Guay, Ratelle, & Chanal, 2008; Searle, Miller-Lewis, Sawyer, & Baghurst, 2013; Skinner & Pitzer, 2012).

Difficulties with motivation have long been implicated in ADHD (Barkley, 1997; Douglas, 1999) with recent neurobiological research highlighting “altered reward sensitivity” in children and adults with ADHD (Sonuga-Barke, 2003, 2005; Sonuga-Barke, Bitsakou, & Thompson, 2010). For instance, children with a clinical diagnosis of ADHD prefer more immediate rewards versus delayed (Sonuga-Barke, 2003) and tend to perform better on cognitive tasks when rewards are provided relative to a no-reward baseline condition (Luman, Oosterlaan, & Sergeant, 2005; Rosch & Hawk, 2013). This positive effect of external rewards on behavior is consistent with theoretical and empirical research documenting links between abnormalities in brain regions involved in attention control, motivation, and reward processing (Cubillo, Halari, Smith, Taylor, & Rubia, 2012; Volkow et al., 2011). Behaviorally, difficulties with motivation in children with ADHD are manifested by lower rates of persistence and effort on academic tasks, and report more frustration when completing challenging tasks than their typically developing peers (Carlson, Booth, Shin, & Canu, 2002; Hoza, Waschbusch, Owens, Pelham, & Kipp, 2001). Homework problems are also common in children with ADHD, manifested as poor planning and organization of time and materials and delay in initiating and completing tasks (Langberg et al., 2010).

Studies examining the association between the behaviors characteristic of poor intrinsic motivation (e.g., low preference for challenge, problems working independently) and ADHD symptoms report that these behaviors are more related to inattention symptoms than hyperactivity-impulsivity symptoms as rated by parents and teachers (Langberg et al., 2010; Power, Werba, Watkins, Angelucci, & Eiraldi, 2006). In fact, children who exhibited a high stable profile of inattentive behavior (11% of sample) from kindergarten to third grade scored significantly lower than those who exhibited a low stable inattention profile (53% of sample) on teacher ratings of academic motivation to learn in fifth grade (Sasser et al., 2015). Overall, this pattern of results suggests that children who display inattentive behavior are likely to exhibit behaviors that reflect poor academic motivation.

To result in academic success, intrinsic motivation for learning must also result in an outward behavioral expression manifested by involvement in a learning activity, called engagement (Reeve, 2012). A recent evaluation of different theoretical perspectives supported the hypothesis that motivation predicts (or precedes) subsequent levels of engagement and, in turn, achievement outcomes (Strand et al., 2012). Although there are multiple forms of engagement (Reschly & Christenson, 2012), we focus here on one type, which has been shown to be the strongest predictor of school achievement and dropout: behavioral engagement (Archambault, Janosz, Morizot, & Pagani, 2009; Archambault & Vandenbossche-Makombo, 2014; Finn & Zimmer, 2012). Behavioral engagement is manifested by observable behaviors such as task persistence, participation in classroom activities, as well as actual completion of homework and test preparation (DiPerna & Volpe, 2002). Children who demonstrate these behaviors in the classroom also tend to show higher levels of academic achievement (Guo, Connor, Tompkins, & Morrison, 2011).

In addition to their distinct motivational profile, children with ADHD also show difficulties in behavioral engagement (Luman, Goos, & Oosterlaan, 2015). The lower behavioral engagement of children with ADHD is manifested by low levels of task persistence during academic tasks (Hoza et al., 2001) and teacher-led instruction (Steiner, Sheldrick, Frenette, Rene, & Perrin, 2014), as well as homework difficulties (Langberg et al., 2010). Difficulties in behavioral engagement could be a manifestation of difficulties in EF, which are thought to be involved in the pathophysiology of ADHD (Barkley, 1997; Sonuga-Barke, 2005). Indeed, difficulties in EF, specifically planning and organization, account for a sizable portion of the association between inattention and homework difficulties as well as grades (Langberg et al., 2013). Working memory, a core EF thought to support goal-oriented behavior (Hofmann, Schmeichel, & Baddeley, 2012), is also implicated in children’s task-focused behavior in the classroom and error monitoring (Gathercole et al., 2008).

Evidence supporting the hypothesis that these intrinsic motivation and behavioral engagement explain the association between ADHD symptoms and academic achievement is generally mixed. In a recent longitudinal study, the link between ADHD symptoms and a global measure of academic achievement was mediated by a construct similar to intrinsic motivation (Portilla, Ballard, Adler, Boyce, & Obradović, 2014). It is unclear, however, if this pattern of results would hold for different academic domains. In a study conducted with a community sample, ADHD symptoms was indirectly associated with reading performance via intrinsic motivation and behavioral engagement, but this was not the case for mathematics (Demaray & Jenkins, 2011). In a clinical sample, there was no evidence of indirect association after accounting for the direct association between ADHD symptoms and achievement in reading and mathematics (Volpe et al., 2006). Differences in the results between these two studies could be due to differences in the sample studied (community vs. clinical sample, respectively) but also due to variations in the informant used to obtain information about ADHD symptoms (parent vs. teacher report, respectively). In summary, it remains unclear whether intrinsic motivation and/or behavioral engagement explain the association between ADHD and academic achievement.

Generally, the studies that have examined inattention symptoms, intrinsic motivation, and behavioral engagement in relation to academic achievement share two limitations. First, all of the studies used a composite score indexing hyperactivity-impulsivity and inattention symptoms rather than inattention symptoms in particular. This is problematic because academic achievement is more strongly associated with inattention symptoms than with hyperactivity/impulsivity (Barriga et al., 2002; Langberg et al., 2013; Pingault et al., 2011). As a result, the use of a composite score that also incorporates hyperactivity and impulsivity may lead to an underestimation of the strength of its relationship with academic achievement. Second, none of the studies included indices of writing achievement despite its associations with inattention symptoms (e.g., Kim et al., 2013) as well as with intrinsic motivation (Troia, Shankland, & Wolbers, 2012). Given that prior findings were inconsistent depending on the domain under consideration (i.e., reading or mathematics), it is important to include writing proficiency as an independent domain of achievement. Our study plans to address these limitations by investigating whether inattention symptoms (reported by both parents and teachers) are indirectly associated with achievement in reading, writing, and mathematics (derived from performance-based assessments) via intrinsic motivation and behavioral engagement.

One potential explanation for the inconsistent findings pertaining to the mediating role of intrinsic motivation and behavioral engagement is that the correlations between ADHD symptoms, engagement, and motivation are substantial (e.g., Volpe et al., 2006). Individual differences in inattention symptoms, intrinsic motivation, and behavioral engagement may be due, at least in part, to shared underlying factors such as shared cognitive deficits (Volkow et al., 2011). As a result, the shared variance across these factors rather than factors unique to one of these constructs is important to examine.

Support for the “shared variance” argument is provided by two studies showing that none of the variables (ADHD symptoms, behavioral engagement, motivation) independently predicted academic achievement in mathematics (Demaray & Jenkins, 2011) and reading performance (Volpe et al., 2006) despite the fact that they were each strongly correlated with the measures of academic achievement. The lack of independent effects implies that it is mostly the variance that is shared among these constructs that is associated with academic achievement. To test this hypothesis, we will first examine the amount of variance shared between inattention symptoms, intrinsic motivation, and behavioral engagement. Next, we will determine whether it is the shared or unique variance associated with these constructs that is associated with academic achievement. Addressing this latter goal is important because a better understanding of the overlap between inattention symptoms, intrinsic motivation, and behavioral engagement will promote our understanding of the factors involved in academic achievement.

The Current Study

Our research objectives were twofold. First, we sought to determine whether inattention symptoms are indirectly associated with academic achievement via intrinsic motivation and behavioral engagement. To rule out the possibility that the observed associations were due to shared rater bias, we used a multi-informant approach. Inattention symptoms were reported by parents and teachers, intrinsic motivation and behavioral engagement were reported by teachers, and academic achievement in reading, writing, and mathematics was assessed using independent performance-based assessments. Given previous findings (Demaray & Jenkins, 2011), we expected intrinsic motivation or behavioral engagement to mediate the association between inattention symptoms and achievement in reading but not mathematics. We did not formulate any hypothesis in the case of writing because no study investigated this academic domain previously.

Our second research objective was to determine the extent to which the association between inattention symptoms and academic achievement is due to variance shared with intrinsic motivation and behavioral engagement or due to variance unique to each of these predictors. Due to the large overlap between inattention symptoms and intrinsic motivation and behavioral engagement, we expected that most of their association with academic achievement domains would be due to their shared variance.

Method

Sample

The participants for this study took part in a larger study examining the effects of providing classroom teachers with professional development on working with students with attention problems in the classroom. The present study is based on data gathered from four schools in a rural school board in Ontario in late February and early March (second term of the school year) prior to the professional developments sessions. For this reason, the effect of the training received by teachers is not considered further. Inclusion criteria for the larger study were that the students had to attend a general education classroom, be proficient enough in English to be able to provide informed assent, and have parental permission to participate. Each participating teacher (n = 16) was asked to identify 6 children for possible recruitment with varying levels of attention skills. Identified children were equally divided among those with good, average, and below average attention skills. Consent packages were sent home to the 96 selected children. Parental consent (and informed child assent) for participation in the larger study was obtained for all 96 students; however, 4 students were not available when testing was conducted. Thus, the participants for the present study include 92 students in Grades 1 to 4 (Grade 1, n = 20; Grade 2, n = 27; Grade 3, n = 22; Grade 4, n = 23). Children were on average 8.21 years old (SD = 1.18). Of the 75 participants whose parent/guardian returned the demographic form, 97.3% indicated that the primary language spoken at home was English and 95.9% reported Caucasian as their ethnicity. There was a slightly larger number of males compared with females (male n = 61; female n = 31). Ethical consent was obtained from the University of Toronto Research Ethics Board and from the participating school board.

Procedure

Teachers were provided with release time to complete the questionnaires on each participating student. Achievement measures were administered by trained graduate students in a quiet setting in the child’s school. As some children were absent on the day of testing, not all children completed all measures. The math and written expression assessments were administered in small groups and the reading assessment was completed individually.

Measures

Inattention symptoms

Teachers and parents completed the Strengths and Weaknesses of ADHD Symptoms (SWAN; Swanson et al., 2006). The SWAN inattention subscale is comprised of nine positively worded statements indexing the nine Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) symptoms of ADHD (Polderman et al., 2007). Each participant was rated on a scale from −3 (well below average) to 3 (well above average) with a score of 0 indicating average levels of the target behavior. The items were reverse coded so that a higher score would indicate greater difficulties. The SWAN inattention score was computed by averaging the scores from the nine items for each participant. In the current study, internal consistency of the inattention symptoms items was excellent for teacher and parent reports, α = .98 and α = .93, respectively. Parent and teacher report were highly correlated (r = .49) and were aggregated. This composite score was age- and sex-regressed prior to all analyses.

Intrinsic motivation and behavioral engagement

Teachers were asked to complete the Academic Competence Evaluation Scales (ACES; DiPerna & Elliott, 1999). The psychometric qualities of the ACES have been found to be satisfactory (DiPerna & Elliott, 1999). The ACES includes five subscales that assess academic enablers, three of which were used in the current study. Intrinsic motivation was measured using the “Motivation” subscale, which includes 10 items such as “is goal oriented,” “looks for challenges,” and “evaluates work.” Two ACES subscales (Engagement and Study Skills) were used to create a behavioral engagement score. The “Engagement” subscale contains 10 items that relate to participation in classroom activities such as “participates in discussion” and “volunteers answers.” The “Study Skills” scale contains 8 items that relate to work completion such as “completes class assignments on time,” “corrects assignments,” and “cares for material.” We averaged the “Engagement” and “Study Skills” scales to create a behavioral engagement score to facilitate comparison with other studies that use definitions of behavioral engagement that focus on active participation as well as homework completion (Reschly & Christenson, 2012). In the current sample, internal consistency on the scales were excellent (α = .94-.98). The intrinsic motivation and behavioral engagement composite scores were age- and sex-regressed prior to all analyses.

Academic achievement

Reading achievement was evaluated using the total score on the Test of Word Reading Efficiency (TOWRE; Torgesen, Wagner, & Rashotte, 1999). This test has the benefit of being normed, which allows us to take into account the varying ages of children. The TOWRE assesses two reading skills: sight word reading efficiency and phonemic decoding efficiency. The current study uses the total scaled scores, which incorporates the two reading skills. All reading tests were scored by trained research assistants. All tests were double-scored and any discrepancies in scores were resolved prior to entry into the database. Mathematics computation proficiency was measured using a brief curriculum-based measure (CBM) of math (Fuchs, Hamlett, & Stecker, 1991). Consistent with administration guidelines (Fuchs et al., 1991), students were given 2 min in first and second grades and 3 min in third and fourth grades to produce responses to 25 basic facts and algorithms connected to curriculum goals in the elementary grades (first-fourth grade). As there are more skills in the upper grades, more time is required for students to complete the assessment as the items are more challenging. Each CBM probe was scored for the number of correct digits per minute. Children received partial credit for a response if at least one of the digits in the response was in the correct place value. All of the CBM probes were scored by a trained graduate student completing a master’s degree in school and clinical child psychology. A second independent trained undergraduate psychology student independently scored the CBM tasks, and any discrepancies in scores were resolved prior to entry into the database.

Written expression was assessed using a brief 3-min CBM probe (Malecki & Jewell, 2003). Each child was provided with a lined piece of paper containing a story starter. The children were given 1 min to plan what they were going to write about and 3 min to compose the story. Children were encouraged to guess if they did not know how to spell a word. Children who stopped writing prior to the time limit were encouraged once by the examiner do to their best. All stories were scored for the total number of words written (TWW) regardless of spelling accuracy and for total words spelled correctly (WSC). The score used in the present study was the percentage of words spelled correctly (WSC/TWW) because this index has been associated with multiple standardized tests of written expression throughout elementary school (Jewell & Malecki, 2005). Two graduate assistants enrolled in a school and clinical child psychology graduate training program were trained in standard scoring procedures for the CBM written expression task (Fuchs & Fuchs, 2007). All CBM writing probes were scored independently by each research assistant following training, and any discrepancies in scores were resolved via discussion and a consensus score was entered into the database.

The external validity of these scores is supported by the associations between teacher reports of performance in language arts with reading achievement (r = .56, p < .001) as well as with writing achievement (r = .42, p < .001). Similarly, teacher reports of performance in mathematics was associated with mathematics achievement (r = .47, p < .001). All achievement scores were age- and sex-regressed prior to analyses.

Analyses

All analyses were conducted in SPSS. As fewer than 5% of the participants had missing data, analyses were conducted on a single imputation (Graham, 2009). Analyses were thus performed using the whole sample. To assess the potential mediating roles of intrinsic motivation and behavioral engagement, we used regression analyses. The significance of the indirect effect was tested using bootstrapping, which is the preferred method to do so (Preacher & Hayes, 2008). The indirect effect is significant when its 95% confidence interval (CI) does not include zero. Three models were tested (one for each academic outcome) in which intrinsic motivation and behavioral engagement were included simultaneously as potential mediators. We report the effect of the predictor on the putative mediators (“a path”), the effect of the putative mediators on the outcome (“b path”) as well as the indirect effects (“a × b”).

Our second objective was to examine the extent to which inattention symptoms were associated with academic achievement due to variance shared with intrinsic motivation and behavioral engagement. To do so, we conducted commonality analyses that can be used to decompose the effects of correlated predictors into common and unique effects (Kraha, Turner, Nimon, Zientek, & Henson, 2012). This type of analysis is useful to understand the associations between predictors and outcomes especially when the predictors are highly correlated (which is expected given the large associations between inattention symptoms, intrinsic motivation, and behavioral engagement found previously in the literature; Kraha et al., 2012). These analyses were done in SPSS using a package developed for this purpose (Nimon, 2010).

Results

Descriptive statistics and correlations between the main study variables appear in Table 1. The correlations reported in Table 1 show that inattention symptoms were associated with all academic achievement domains. The correlations between inattention symptoms and academic achievement domains were moderate to large in magnitude, ranging from r = −.45 to r = −.54. Inattention symptoms were associated with the hypothesized mediators, intrinsic motivation, and behavioral engagement, at r = −.87 and r = −.85, respectively. Next, we examined whether inattention symptoms were associated with each of the academic achievement domains indirectly via behavioral engagement and intrinsic motivation. These analyses appear in Table 2. Results indicated that none of the direct effects of the putative mediators (the b paths) were significant indicating that the variables did not contribute additional variance to the academic outcomes once controlling for behavioral inattention. Moreover, none of the indirect effects were significant (see column a × b). Overall, this pattern of findings suggests that the associations between the putative mediators (behavioral engagement and intrinsic motivation) and academic achievement domains are entirely due to variance shared in common with inattention symptoms. The high overlap among the three predictors was also shown in slightly elevated multicollinearity statistics, with variance inflation factor (VIF) values between 4.45 and 6.75.

Table 1.

Correlations, Means, Standard Deviations and Number of Observations for All Study Variables.

	1.	2.	3.	4.	5.	M	SD	n
Inattention symptoms						−0.10	1.12	89
Motivation	−.87*					33.68	10.91	88
Engagement	−.85*	.91*				31.64	7.65	88
Reading (standard score)	−.45*	.48*	.45*			98.74	14.68	92
Writing (% of words spelled correctly)	−.46*	.46*	.43*	.50*		0.78	0.16	92
Mathematics (digits correct per minute)	−.54*	.55*	.54*	.29*	.45*	9.04	6.85	92

Note. Correlations are based on the age- and sex-regressed variables, and means and standard deviations are based on the raw variables.

p < .05.

Table 2.

Indirect Effects Linking Inattention Symptoms and Academic Achievement Domains via Intrinsic Motivation and Behavioral Engagement.

	a path (SE)	b path (SE)	Indirect effect (a × b)	95% CI
Mathematics
Via behavioral engagement	−.85 (.06)	.14 (.23)	−.12	[−.57, .35]
Via intrinsic motivation	−.86 (.05)	.23 (.24)	−.20	[−.77, .27]
Reading
Via behavioral engagement	−.85 (.06)	.02 (.24)	−.02	[−.36, .34]
Via intrinsic motivation	−.86 (.05)	.34 (.25)	−.30	[−.75, .12]
Writing
Via behavioral engagement	−.85 (.06)	−.01 (.24)	.01	[−.41, .48]
Via intrinsic motivation	−.86 (.05)	.28 (.25)	−.24	[−.66, .12]

Note. All effects can be interpreted as standardized regression weights. a path = effect of inattention symptoms on the putative mediator. b path = effect of the putative mediator on the academic achievement outcome (controlling for the effect of inattention symptoms).

Commonality Analyses

We then performed commonality analyses to reach our second objective. One analysis was performed for each academic outcome separately. Results for these analyses appear in Figure 1. Together, behavioral inattention, intrinsic motivation, and behavioral engagement accounted for R² = .33, R² = .25, and R² = .22 of the total variance in mathematics, reading, and writing, respectively. The commonality analyses indicated that the majority of the variance accounted for by the predictors was due to variance shared by all three predictors (R² = .27 for mathematics, R² = .19 for reading, and R² = .18 for writing). This means that between 77.44% and 82.10% of the total variance accounted for by the three predictors was due to variance shared among all of them. Variance shared among two predictors explained a smaller proportion of the total variance accounted for by the predictors (R² = .01 to .02 for mathematics, R² = .00 and .02 for reading, and R² = .00 and .02 for writing). Individual variables contributed little unique variance (R² = .004 and .01 for mathematics, R² = .004 and .02 for reading, and R² = .00 to .02 for writing). Thus, the academic achievement outcomes were mostly predicted by variance shared among all three predictors, whereas variance shared between pairs of predictors or unique to each predictor made much smaller contributions.

Figure 1.

Variance explained (in terms of R²) in each achievement domain by unique and shared variance among the predictors: (a) Mathematics, (b) reading, and (c) writing.

Discussion

Given the considerable evidence demonstrating that inattention symptoms are robust indicators of concurrent and future academic difficulties (Duncan et al., 2007), it is important that we better understand the nature of the relationship between inattention symptoms and academic achievement. In this study, our goal was to investigate the potential mediating role of intrinsic motivation and behavioral engagement in the association between inattention symptoms and academic achievement, as well as to examine the common and unique contributions of the three predictors to academic achievement.

In the present study, data indicated that inattention symptoms were not associated with academic achievement indirectly via intrinsic motivation and behavioral engagement. Contrary to our expectations, these results did not vary as a function of the academic domain under consideration. Although some studies have also reported similar results (Demaray & Jenkins, 2011; Volpe et al., 2006), other studies have supported the presence of an indirect association (Demaray & Jenkins, 2011; Portilla et al., 2014). The latter two studies differed in two ways from the current study. First, they both used a composite score of ADHD symptoms rather than a measure of inattention symptoms (Demaray & Jenkins, 2011; Portilla et al., 2014). This methodology may increase the likelihood of finding that intrinsic motivation and behavioral engagement contribute to academic achievement over and above ADHD symptoms, because the association between ADHD symptoms and achievement domains may be lower than the association between inattention symptoms and academic achievement. Second, the study by Demaray and Jenkins (2011) used parent ratings of child ADHD symptoms whereas we used a composite score comprising both parent and teacher reports. It is possible that the use of multiple informants to measure inattention symptoms resulted in a more reliable and stable pattern of association with academic achievement domains. Given that most of these studies including the present investigation used a cross-sectional design, it will be important to investigate the proposed mediation model within a longitudinal design to accurately disentangle the direction of associations between inattention symptoms, intrinsic motivation, and behavioral engagement.

The second major finding of the study was evidence showing that academic achievement domains were mostly predicted by variance shared among inattention symptoms, intrinsic motivation, and behavioral engagement. In total, between 77.44% and 82.10% of the total variance explained in each academic achievement domain was due to variance common to the three predictors. This result suggests that we should focus on the variance that is shared between inattention symptoms, intrinsic motivation, and behavioral engagement rather than on the small portion of unique variance explained by each of the three predictors.

The substantial empirical overlap between inattention symptoms, intrinsic motivation, and behavioral engagement has received relatively little attention in developmental/clinical psychology or education. These large associations raise important questions about the mechanisms accounting for this overlap. Currently, theoretical models typically assume that ADHD symptoms predict subsequent levels of intrinsic motivation and behavioral engagement, which in turn predict academic achievement (Volpe et al., 2006). However, studies investigating this temporal sequence within a longitudinal framework are rare (for an exception, see Portilla et al., 2014).

There are at least two other explanations that may account for the link between inattention symptoms, intrinsic motivation, and behavioral engagement beside mutual influences. First, these constructs may have common etiological factors. Notably, neuropsychological factors including EF have been associated with all three constructs (Brock, Rimm-Kaufman, Nathanson, & Grimm, 2009; Hughes & Ensor, 2011; Martinussen, Hayden, Hogg-Johnson, & Tannock, 2005; St Clair-Thompson & Gathercole, 2006). Executive functions encompass a variety of cognitive processes that are involved in the planning of complex behaviors, control of attention as well as self-regulation of behavior, and emotions (Wade, Browne, Madigan, Plamondon, & Jenkins, 2014). There is also direct evidence that inattention symptoms and motivation are associated with common neuropsychological factors that include individual differences in the dopamine reward pathway (Volkow et al., 2011). The presence of shared cognitive deficits between motivation and inattention is further supported by recent studies demonstrating that improvements in sustained attention can be observed when children with ADHD are provided with extrinsic reinforcement (e.g., external rewards) or psychostimulants (Bubnik, Hawk, Pelham, Waxmonsky, & Rosch, 2015); the latter of which have been shown to increase individuals’ reported interest in tasks via increased dopamine availability in the brain (Volkow et al., 2004). The identification of shared neuropsychological factors raises the possibility that inattention symptoms are neither a cause nor a consequence of intrinsic motivation and behavioral engagement, but rather an indicator of neuropsychological difficulties that are also associated with intrinsic motivation and behavioral engagement. It will be necessary to investigate this possibility further using a longitudinal design using multiple informants to assess each construct (e.g., child and teacher reports of intrinsic motivation).

Second, it is also possible that measures of intrinsic motivation and behavioral engagement capture symptoms of inattention to some extent. For instance, inattentive children have difficulty sustaining attention for an extended period of time (Hoza et al., 2001), which may be perceived by an observer as a lack of motivation for an activity and a lack of engagement in that activity. Also, children with ADHD tend to avoid mental work that requires effort (Carlson et al., 2002), which could be seen as a lack of behavioral engagement by educators. This measurement overlap is further complicated by the fact that there is no clear definition of student engagement and, as a result, no consensus on how to measure it (Eccles & Wang, 2012; Reschly & Christenson, 2012). A better understanding of the mechanisms that explain the associations between inattention symptoms, intrinsic motivation, and behavioral engagement may be achieved by undergoing extensive work on the measurement of these constructs.

The current results have several implications. First, these results suggest that future studies should explore neuropsychological factors that influence children’s behavioral engagement and intrinsic motivation. It is possible that children who are viewed as having low intrinsic motivation are sensitive to reward delay and frequency and the presence (or absence) of reinforcing task features. These results also raise the possibility that children with low intrinsic motivation and low behavioral engagement could benefit from the same interventions that are beneficial for inattentive children. For instance, children’s inattention is less strongly linked with reading and mathematics performance when teachers are more emotionally supportive (Rudasill, Gallagher, & White, 2010). Task performance in children with ADHD is also higher when task parameters are modified to be more interesting or novel (Beike & Zentall, 2012).

The current results may encourage researchers from psychology and education to draw on these largely separated bodies of research (inattention symptoms, student behavioral engagement) to disentangle these various constructs across development (e.g., early school years, adolescence). We posit that research integrating social, contextual, and individual factors will help bridge research from psychology and education, potentially resulting in a better understanding of the processes supporting children’s academic achievement. For example, Searle et al. (2013) examined the relations between the quality of the relationships between adult–child relationship (teacher, parent) and behavioral engagement. Of particular relevance to the present study was the finding that the association between relationship quality and engagement was only indirectly related to engagement through hyperactivity/inattention. These findings suggest a need to measure inattention symptoms in studies examining predictors of behavioral engagement and motivational factors.

The current study has multiple strengths. First, children’s inattention symptoms were based on both parent and teacher reports, which may result in a more comprehensive description of child functioning across a variety of contexts. Second, we used objective assessments of academic achievement to rule out the possibility that their association with child behaviors would be due to shared rater bias. Third, we used brief CBM probes to assess mathematics computation skills and writing proficiency, which may be more representative of the content seen in schools than performance-based assessments (Elliott & Fuchs, 1997).

This study is also not without limitations. Notably, we used a cross-sectional design, thereby preventing us from making conclusions with regard to the direction of effects. We also did not measure children’s intrinsic motivation and engagement in each academic domain. However, there is evidence that behavioral engagement does not differ according to academic content domain (Archambault & Vandenbossche-Makombo, 2014). There is also evidence that academic motivation across different academic domains is less differentiated in children than adolescents (Bong, 2001), suggesting that a general measure of motivation is more justifiable in children than in adolescents. Domain-specific measures may be needed to further delineate more specific associations between inattention symptoms, intrinsic motivation, and behavioral engagement. Finally, the strategy used to recruit participants in the study based on teacher nomination could have influenced the nature of the current sample. Other studies are needed to verify whether the results obtained in the current study are generalizable in clinical samples as well as in unselected community samples.

Conclusion

Results from the current study did not support the hypothesis that intrinsic motivation and behavioral engagement mediated the relation between behavioral inattention and academic achievement. Rather, the commonality analyses indicated that it was the variance that was common to behavioral inattention, intrinsic motivation, and behavioral engagement that accounted for the largest proportion of total variance in the academic outcomes measures. We found that 77.44% to 82.10% of the variance accounted for by the predictors was shared by inattention, behavioral engagement, and intrinsic motivation. More research is needed to clarify the extent to which inattention symptoms, intrinsic motivation, and behavioral engagement differ at a behavioral level to clarify the causal links between those constructs as well as the nature of their associations with academic achievement.

Footnotes

Acknowledgements

The authors thank the teachers and students who participated in this study as well as the schools and parents who made it possible. They also acknowledge the contribution of Julia Ferrari, Madison Aitken, and Daniel Pignon in the data collection. They also thank Dr. Rosemary Tannock for her helpful comments on an earlier version of the manuscript.

Authors’ Note

Any opinions, findings, and conclusions expressed in the article are those of the authors and do not necessarily reflect the views of the sponsoring agencies.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This study was supported by a grant from The Provincial Centre of Excellence in Child and Youth Mental Health (Ontario) Grant # RG-626 to Dr. Rosemary Tannock and Mary Anne Alton (Co-PIs).

Author Biographies

André Plamondon, PhD, is an Assistant Professor in the Faculty of Education, Laval University, Canada. His current research interests include the mechanisms linking ADHD symptoms and impairments in school functioning, executive functions as well as the interplay between biological, social, and contextual factors in developmental psychopathology.

Rhonda Martinussen, PhD, is an Associate Professor in the Department of Applied Psychology and Human Development at the Ontario Institute for Studies in Education at the University of Toronto in Toronto, Ontario, Canada. Her research examines academic, cognitive, and motivational processes in children and youth with ADHD. She also is active in research investigating knowledge mobilization in the education system to enhance the learning environment for children with learning and attention difficulties.

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