Annefleur Kortekaas Rijlaarsdam

The results from our double-blind randomized placebo-controlled crossover study comparing the immediate (7-days treatment) effects of long-acting MPH and placebo are in line with the findings from the meta-analysis and were described in Chapter 3. Here, we investigated the impact of ADHD on academic performance and the effects of MPH on academic accuracy and productivity in math, reading and spelling. Children with ADHD (N=63, age 8-13, IQ>70) were impaired on math accuracy and productivity compared to TD children (N=67, age 8-13, IQ>70). The effects of MPH were small- to medium sized and limited to those academic subjects for which children with ADHD significantly underperformed in comparison to TD children (math). For mathematical productivity, MPH treatment resulted in a 2% increase, but performance did not normalize to the level of TD children. Further, MPH treatment increased accuracy for mathematical word problems by 9% and so doing normalized performance of children with ADHD to the level of TD children. Together, the results from the meta-analyses and our RCT reveal that academic improvements with MPH in children with ADHD are small compared to symptom improvements (which were medium- to large in this study) and qualitative improvements were limited to math.

SECOND AIM

The Mechanism behind MPH-effects on Academic Performance
In the meta-analysis described in Chapter 2, we investigated the mediating and moderating effect of behavioral improvements (mediator) and demographic-, design-, and disorder-related variables (moderators). The number of studies reporting on these mediators and moderators was limited, therefore our meta-regression analyses were conducted for the effects of MPH on math accuracy only. Further, the number of studies reporting on on-task behavior and parent-rated improvements in ADHD symptoms was insufficient for meta-regression. Our results from the meta-regression of 29 studies on MPH effects on math accuracy reveal no mediating effect of teacher-rated ADHD symptom improvements. None of the included moderators (age, gender, ADHD-subtype, ODD/CD comorbidity, ADHD severity, release system, study duration, time of measurement, dose and titration method) affected the effect of MPH on academic performance. Thus, the meta-regression of existing studies reported provides no evidence for effects of the hypothesized behavioral mediators and demographic-, design-, and disorder related moderators. However, more research on this topic is necessary to investigate the effects of potential mediators and moderators on other academic outcomes (e.g. math productivity, reading accuracy and productivity).

In Chapters 3 and 4 we further investigated the mechanism behind MPH-related improvements in academic performance. Data was obtained from the abovementioned RCT investigating the short-term effects of MPH on academic performance in a group of children with ADHD. Specifically, the mediator and moderator analyses in these chapters focused on math productivity and math accuracy as these measures showed significant (albeit small) improvement with MPH treatment. In Chapter 3, we investigated the mediating effect of ADHD symptom improvements on the relation between MPH treatment and math performance. In addition, this chapter describes the moderating effects of learning ability and ADHD symptom severity on MPH-related math improvements. In line with our hypothesis, parent-rated symptom improvements partially mediated the effects of MPH on math productivity. Parent-rated symptom improvements did not affect MPH-improvements in math accuracy. Also, teacher-rated improvements in ADHD symptoms did not influence MPH-effects on math accuracy or math productivity. The former is in line with the results from the meta-analysis. Moreover, MPH efficacy in improving math accuracy in this study was limited to children with lower-than-average mathematical abilities. Our results implicate that ADHD symptom severity (attentional and hyperactive/impulsive symptoms) did not moderate the effects of MPH on math performance. Thus, the results from Chapter 3 suggest that the small effects of MPH on math performance are, at least in part, due to improvements in ADHD symptoms.

In Chapter 4, we expanded the findings of Chapter 3 by exploring the mediating effects of MPH-related improvements in cognition, motivation and perceived competence on MPH effects on math performance. The results from this study indicate that children with ADHD perform worse than TD children on cognitive measures thought to be important in determining academic performance, including visuospatial working memory and lapses of attention. Moreover, children with ADHD showed lower intrinsic motivation for schoolwork, specifically for math. In addition, children with ADHD showed altered parent-rated reward responsivity and lower self-, parent- and teacher rated self-perceived competence. In contrast to our hypotheses, MPH improved neither cognition nor motivation for schoolwork. Thus, this study did not provide evidence for a mediating role for cognitive or motivational improvements on MPH-related effects on math. Our results did show that MPH increased parent-ratings of their child’s self-perceived competence and these improvements mediated MPH efficacy on math productivity. Together, the results from our RCT demonstrate that the limited effects of MPH on math productivity are at least partly due to behavioral improvements, whereas such behavioral improvements (teacher- and parent-rated) do not affect MPH effects on math accuracy. Further, the results from Chapter 4 raise questions about how necessary improvements in specific cognitive and motivational deficits associated with ADHD are for medication-related academic improvement.

THIRD AIM

Effects of MPH on Feedback Learning and on the Ability to Profit from Reward
The third aim was to quantify the effects of MPH on two aspects of reinforcements processing in children with ADHD: Firstly, the effects of MPH on feedback learning were studied (Chapter 5) and secondly, the interaction between MPH and reward on math performance was investigated (Chapter 6). For both studies, data were obtained from the abovementioned RCT comparing performance of 63 children with ADHD while treated with MPH or placebo, and comparing their performance to that of 67 TD controls. To study the effects of MPH on feedback learning, a well validated associative learning test adapted for children was used: The task started with a learning phase during which novel stimulus-reward associations were learned, and was followed by a test phase during which the acquired knowledges had to be applied to novel stimulus pairs. The task ended with a reversal phase in which contingency values were reversed. Using this task, the effects of ADHD diagnosis and MPH treatment on the acquisition of stimulus-reward associations, generalization of this knowledge to novel contexts and reversal learning were studied. The results suggest that both the acquisition of stimulus-reward associations and reversal learning are intact in children with ADHD. However, children with ADHD showed impairments in generalization of acquired knowledge. Treatment with MPH improved the acquisition of novel stimulus-reward associations and there was a trend effect of MPH on generalization of knowledge. MPH normalized the ability of children with ADHD to generalize knowledge to the level of TD peers. In conclusion, these result reveal that the acquisition of knowledge with feedback learning is intact in children with ADHD but that they face difficulties when applying this knowledge to novel contexts. Medication has potentially beneficial effects on feedback learning in ADHD in a way that may lead to improvements of generalization of stimulus-reward associations. However, replication of these results is necessary.

In Chapter 6 we compared the effects of reward and MPH, and the possible interaction between them, on an ecologically valid math performance task in children with ADHD. To this end, we developed a math task that required children with ADHD and TD controls to solve calculations (addition) of increasing difficulty level. Difficulty was adapted to performance and performance was either coupled to contingent reward (motivation condition: a smiling face; the sound of applause; +1 point which could be exchanged for stickers) or no feedback (neutral condition). Achieved difficulty level at the end of the task was the dependent variable. The results from this study indicate that all children profited equally from rewarded feedback, resulting in better math performance. The effects of MPH and rewarded feedback on math performance were additive. In line with the results from the meta-analysis and Chapter 3, children with ADHD were impaired on the math task compared to TD controls. However, children with ADHD did not profit more from feedback than TD controls did. These results emphasize the importance of motivational strategies such as positive feedback and small rewards to improve academic performance in both children with and without ADHD.

General Discussion and Implications of the Results
This thesis aimed to further investigate the effects of MPH, the most common stimulant for ADHD, on academic performance and learning. Key outstanding questions are (1) whether MPH affects the quality of academic work or merely results in increased effort; (2) whether the effects of MPH differ between core academic subjects; (3) whether improvements in behavior, cognition and motivation mediate the effects of MPH on academic performance; (4) how MPH affects feedback learning and the ability to profit from feedback and reward. This knowledge is necessary to manage the expectations of treating physicians, parents and teachers. Further, knowledge of moderators of the effects of MPH on academic performance could result in the identification of clinical subgroups for which higher or lower medication effectivity could be expected.

MPH has Very Limited Effects on Academic Performance in Children with ADHD
Our results reveal that improvements with MPH can be achieved over the short term (RCT with treatment duration of one week) but are very specific and limited to math (according to the meta-analysis and our experimental data) and reading (according to the meta-analysis). These results thus stress the importance of distinguishing between academic subjects (math, reading, spelling) when studying the effects of MPH on academic performance. Specifically, the results from our meta-analysis suggest that the potential for MPH to improve academic performance lies in those areas where underperformance is most apparent (i.e. math and reading, see also Frazier, Youngstrom, Glutting, & Watkins, 2007). This suggestion is confirmed by our findings from Chapter 3 showing that MPH improved academic performance only in those subjects (math productivity and accuracy) where children with ADHD underperformed in comparison to TD children. One explanation for the subject-specific effects of MPH on academic performance may be the focus of current research: Studies on the effects of MPH focus on math and reading and rarely report on other academic subjects (e.g. spelling, writing). Thus, perhaps the current amount of research is too little to reveal positive effects of MPH.

Table 7.1 Overview of the thesis aims and corresponding key findings

Aim: 1st aim
Quantify the effects of MPH on academic performance assessed in terms of both productivity and accuracy while distinguishing between core academic subjects (math, reading and spelling)
Key findings:
• MPH has small to medium sized positive effects on math accuracy and math productivity (Chapters 2, 3 and 6) and reading speed (Chapter 2)
• MPH has no effect on reading accuracy and spelling (Chapters 2 and 3)
• Overall academic effects of MPH are small compared to behavioral effects and limited to math (Chapters 2 and 3)

Aim: 2nd aim
Unravel the mechanism behind MPH-effects on academic performance, thereby distinguishing between academic productivity and academic accuracy for math, reading and spelling
Key findings:
• Children with ADHD have cognitive impairments (visuospatial working memory and lapses of attention), and are less intrinsically motivated for math (Chapter 4)
• MPH has large effects on ADHD symptoms (Chapter 3)
• There are no effects of MPH on cognition and motivation (Chapter 4)
• The only evidence for mediating variables influencing MPH-effects on academic performance relates to improvements in ADHD symptoms (parent-rated) and improvements in parent reports of their child’s perceived competence. These effects are specific for MPH effect on math productivity (Chapters 3 and 4).
• Evidence for moderating variables affecting MPH effects on academic performance is limited to math ability: Children with below-average math performance profit more from MPH treatment than children with above-average math performance (Chapter 3).

Aim: 3rd aim
Quantify the effects of MPH on feedback learning in children with ADHD and the interaction between MPH and reward on math performance in children with ADHD
Key findings:
• Children with ADHD show intact acquisition of stimulus-reward associations and reversal learning compared to TD controls (Chapter 5)
• Children with ADHD are impaired when acquired knowledge needs to be applied in novel contexts (Chapter 5)
• MPH treatment improves learning of stimulus-reward associations and shows potential (trend effect) to improve generalization of knowledge (Chapter 5)
• Parents of children with ADHD report differential responses of their children to punishment and reward, compared to parents of TD controls (Chapter 4)
• Children with ADHD and TD controls profit equally from positive feedback and reward, resulting in better math performance (Chapter 6)
• MPH treatment does not affect the ability to profit from feedback and reward on a math task (Chapter 6)

However, results from individual studies so far don’t support the potential of MPH to improve spelling (Bental & Tirosh, 2008; Douglas et al., 1986; Pelham et al., 1985) or writing (Lufi & Gai, 2007) in children with ADHD. Another explanation is that the observed improvements are mostly improvements in productivity. Perhaps reading and math allow for improved productivity more than subjects such as spelling and writing, in which accuracy is more relevant. In keeping with this explanation, math and reading abilities may be more sensitive to short-term (direct) effects of MPH, whereas improvements in for instance handwriting may be achieved only over the longer term as these are more skills based. For example, previous studies showed that handwriting not only depends on sustained attention, but also on fine-motor skills and visual-motor integration (Feder & Majnemer, 2007).

With regard to the effects of MPH on reading abilities, results from our meta-analysis reveal that MPH has the potential to improve reading speed but not accuracy. Our experimental data do not support this view. This may be due to methodological differences between the two studies - in the meta-analysis reading comprehension tasks (reading in story format) were used, while we used a word-reading task in our RCT (technical reading). Although reported correlations between word-reading tasks and reading comprehension are generally high (Aarnoutse, Van Leeuwe, Voeten, Van Kan, & Oud, 1996; Riedel, 2007a), there is also a considerable number of children who show impaired reading comprehension but adequate reading fluency on word-reading tasks (Riedel, 2007b). Thus, measures of reading comprehension may be of most interest here, as reading comprehension is often seen as the ultimate goal for reading achievement (Good, Simmons, & Kame’enui, 2001). However, evidence from earlier studies into ADHD-related impairments in reading do not distinguish between word-reading and reading comprehension (Arnold, Hodgkins, Kahle, Madhoo, & Kewley, 2015; Frazier, Youngstrom, Glutting, & Watkins, 2007). Therefore, it remains unclear whether children with ADHD are more impaired in reading comprehension or word-reading. Taken together, although the increase in reading speed in story format is promising, current literature suggests that such improvements in productivity do not result in qualitative better reading on the short-term or long-term (Langberg & Becker, 2012).

Overall, MPH related improvements in academic performance are small compared to the robust effects of this type of medication on ADHD symptoms (MTA-group, 1999b; Van der Oord et al., 2008). Our findings, combined with evidence relating to MPH effects on longer-term academic outcomes (Langberg & Becker, 2012), raise questions about the value of these MPH-related improvements in math and reading for educational outcomes of children with ADHD. The explanation for the discrepancy between effects of MPH on behavior (ADHD symptoms) and academic performance may lie in clinical titration practices. Medication is titrated on behavioral outcomes (parent- and teacher-ratings of ADHD symptoms), not on cognitive or academic outcomes. However, previous research suggests that medication dose optimal for ADHD symptom improvements is higher than optimal dose for cognitive improvements (Hale et al., 2011). These findings are in line with the smaller effects sizes (often medium sized) for cognitive improvements than for behavioral improvements (Coghill, Seth, et al., 2014; Pietrzak et al., 2006; Van der Oord et al., 2008). In our meta-analysis, we included studies using clinical titration methods as well as studies comparing fixed doses (high versus low). Because we aimed to investigate the maximum possible effects of MPH we selected the doses optimal for academic performance from the latter group. However, this was only possible for 9 out of 34 studies. It is therefore likely that medication doses in the other studies as well as in our RCT were suboptimal for cognitive and academic improvements.

Evaluation of the Proposed Mediation Model
The second aim of this thesis was to unravel the mechanism behind MPH-related improvements in academic performance. The results from our meta-analysis (Chapter 2) and RCT (Chapters 3 and 4) imply that our proposed model was largely incorrect. Although we found evidence for a mediating role for parent-ratings of ADHD symptoms and parent-ratings of their child’s perceived competence, our other mediators and moderators were not significant, see Figure 7.1. This is surprising given the impact of these variables on academic performance and that children with ADHD are impaired on these variables. It is important to note here that the actual effects of MPH on academic performance were minimal. Consequently, this reduces the importance of the mechanism behind such improvements and limits the potential influence of these potential mediators and moderators. Together, these results suggest that improvements in academic productivity at least partly depend on reductions in ADHD symptoms, whereas behavioral improvements do not result in qualitative improvements in academic performance per se.

Figure 7.1 In this thesis we proposed that MPH-related improvements in academic performance could be partly explained by (1) reductions in ADHD symptoms; (2) improvements in cognition (attention, working memory, interference control and processing speed); (3) increases in academic motivation and self-perceived competence. Our results do not support this model. Results from our RCT suggest a mediating role for parent-rated improvements in ADHD symptoms and parent-rated increases in their child’s self-perceived competence.

A puzzling finding in this mediator analysis is that these mediational effects were limited to parent-ratings of symptom improvements and self-perceived competence. In our RCT, parents reported larger reductions in ADHD symptoms than teachers and only parent-ratings of MPH-related increases in perceived competence were significant. The difference between parent- and teacher-ratings of ADHD symptoms and self-perceived competence may be because parents generally spend more time with their child and observe their child in different settings, compared to teachers who often work part-time. As a result, parents may be better in detecting changes in their child’s behavior than teachers (Shemmassian & Lee, 2012) and may be more reliable judges of symptom improvements. However, although the difference between parent- and teacher ratings of ADHD symptoms is also observed in the literature, studies also stress the importance of using multiple informants for the identification of the full range of ADHD symptoms (Mitsis, Mckay, Schulz, Newcorn, & Halperin, 2000). This supports our approach in investigating multiple (parent-, teacher- and sometimes child-) perspectives on our proposed mediators. Concerning the second mediator, self-perceived competence, it might be argued that parents are a reliable source of information here as children with ADHD often give extremely positive reports of their own competence, i.e. they show an illusory bias (Owens, Goldfine, Evangelista, Hoza, & Kaiser, 2007).

In contrast to our predictions, MPH did not improve the cognitive or motivational functioning of children with ADHD in our sample. This was in spite of the fact that children performed less well on these measures, compared to TD controls. These findings oppose previous findings on MPH-related improvements in cognition (Coghill et al., 2014; Pietrzak et al., 2006) and motivation (Shiels et al., 2009). Although our cognitive tasks were comparable in design as task used in previous studies,