Retrospective Report of Academic Motivation Among College Students With Elevated ADHD Symptoms

Abstract

Objective:

Children with ADHD exhibit deficits in academic motivation compared to their peers. Yet conceptualizations of motivation according to prominent motivation theories connected to achievement have not been studied in college-bound youth with ADHD symptoms.

Method:

This study examined motivation according to these theories, differences in motivation by ADHD symptoms, and how the cross-sectional association between motivation and achievement varies by ADHD symptoms. The sample included 461 first-year college students retrospectively reporting their motivation and achievement in their last year of high school.

Results:

Results indicated differences in motivation by ADHD symptoms. Mastery achievement goal orientation was uniquely associated with achievement and exerted beneficial effects on achievement at moderate to high ADHD symptom levels.

Conclusion:

Motivation may operate differently in association with achievement for college-bound youth with ADHD symptoms compared to youth with no to low symptoms.

Keywords

motivation ADHD adolescent academic achievement

There are several prominent motivation theories in the literature that have been evaluated and used to inform educational interventions with typically developing students (Hulleman & Harackiewicz, 2009). This research has been extended to include youth with ADHD, with researchers documenting motivational deficits in elementary and middle-school aged youth with ADHD (see Smith & Langberg, 2018). However, work examining the connection between academic motivation and achievement among high school- and college-aged adolescents with ADHD is lacking (Smith & Langberg, 2018). Motivation is theorized as a key deficit for students with ADHD at all ages (Barkley, 1997), and adolescents with ADHD face unique contextual demands that negatively influence academic functioning (e.g., difficulties with organization and time-management). Yet, little is known about motivation among college-bound adolescents with ADHD who evidence adequate achievement to matriculate to college but still evidence deficits in academic functioning compared to their peers without ADHD (Burr et al., 2022). Such work may inform development of interventions targeting the academic functioning of adolescents with elevated ADHD symptoms to improve their school trajectories.

Theories of Motivation

Motivation is connected to academic achievement (Nicholls, 1979), and many theories exist that seek to understand students’ motivation to achieve. Two prominent theories in the literature are achievement goal theory (e.g., students are motivated to achieve for a specific goal; Dweck, 1986) and the expectancy-value-cost (EVC) model (e.g., students’ motivation is determined by how well they expect to do, how much they value the task, and costs associated with performing the task; Barron & Hulleman, 2014). Each theory has implications for motivation-focused interventions for youth with ADHD. Table 1 presents definitions of motivation terms used in this paper to assist with disentangling theories, terms, and their utility. In addition, across theories of motivation, sex differences in motivation have been found among typically developing students (Meece et al., 2006). Research indicates that typically developing males exhibit higher motivation for math and science compared to females, and typically developing female students exhibit higher motivation for language arts and writing (see Meece et al., 2006).

Table 1.

Motivation Terms Glossary.

Term	Definition
Achievement goal theory	A theory of motivation that states that students adopt a general purpose for achieving (i.e., an achievement goal; Dweck, 1986), either to develop competence by acquiring knowledge or skills (i.e., mastery) or to demonstrate competence relative to others (i.e., performance; Ames, 1992).
Mastery	A construct of achievement goal theory whereby students are motivated based on a desire to develop competence by acquiring knowledge or skills (Ames, 1992).
Performance approach	A construct of achievement goal theory whereby students are motivated based on a desire to be judged as competent relative to peers (e.g., performing the best; Elliot & Church, 1997).
Performance avoidance	A construct of achievement goal theory whereby students are motivated based on a desire to avoid being judged as incompetent relative to peers (e.g., performing the worst; Elliot & Church, 1997).
Expectancy-value-cost (EVC) model	A model of motivation stating that motivation is a function of a student’s expectancy that they can be successful, the value they place on engaging in the task, and the costs associated with engaging in the task (Barron & Hulleman, 2014)
Expectancy	A construct of the EVC model, expectancy incorporates students’ belief in their ability (Eccles & Wigfield, 1995).
Value	A construct of the EVC model, value captures students’ desire to engage in a task due to intrinsic interest (Eccles et al., 1998).
Cost	A construct of the EVC model, cost includes negative factors a student must experience to achieve (Barron & Hulleman, 2014).
Expectancy-value theory	A theory of motivation stating that motivation is a function of a student’s belief, or expectancy, that they can be successful and the value they place on engaging in the tasks required to be successful (Eccles, 2005).

Achievement Goal Theory

In achievement goal theory, students adopt a general purpose for achieving (i.e., an achievement goal; Dweck, 1986), either to develop competence by acquiring knowledge or skills (i.e., mastery) or to demonstrate competence relative to others (i.e., performance; Ames, 1992). Performance goals have been delineated into performance-approach, where students desire to be judged as competent relative to peers (e.g., performing the best), and performance-avoidance, where students desire to avoid being judged as incompetent relative to peers (e.g., performing the worst; Elliot & Church, 1997).

Mastery goals (i.e., acquiring knowledge for competence) are associated with engagement in activities that enhance learning and are assumed to be adaptive. Performance goals (i.e., acquiring skills to perform better or not worse than others) are assumed to be maladaptive due to their reliance on others’ performance rather than striving to achieve for the sake of gaining knowledge or skills (Ames, 1992). Others assert that adopting both mastery and performance goals can be adaptive for helping students achieve (see Barron & Harackiewicz, 2001; Harackiewicz et al., 2002).

Expectancy-Value-Cost Model

In the EVC model, expectancy, value, and cost are the components that influence a student’s motivation (Barron & Hulleman, 2014). This model was derived from expectancy-value theory, where motivation is a function of a student’s belief, or expectancy, that they can be successful and the value they place on engaging in the tasks required to be successful (Eccles, 2005). Expectancy incorporates students’ belief in their ability (Eccles & Wigfield, 1995). Value captures students’ desire to engage in a task due to intrinsic interest (Eccles et al., 1998).

Cost, or negative factors a student must experience to achieve (e.g., giving up time spent with friends to do homework), emerged as a distinct factor based upon empirical work suggesting it is a separate but related construct to expectancy and value (see Barron & Hulleman, 2014; Eccles & Wigfield, 1995). In this theory, having high levels of expectancy and value and low levels of cost would be considered adaptive because they help students achieve.

Among typically-developing students, EVC constructs are associated with various indicators of academic achievement. Expectancy (i.e., belief in ability to be successful) has been implicated as modestly to moderately associated with grades (Simpkins et al., 2006), test scores (Kosovich et al., 2015), and college attendance (Eccles et al., 2004). Value (i.e., intrinsic interest) has been modestly associated with college course grades (Hulleman et al., 2008) and modestly to moderately associated with middle school test scores (Kosovich et al., 2015). Cost (i.e., negative factors associated with achieving) has also been modestly to moderately associated with middle School test scores (Jiang et al., 2018; Kosovich et al., 2015). Thus, like aspects of achievement goal theory, elements of the EVC model were also found to be associated with aspects of achievement.

ADHD and Motivation

Barkley (1997) theorized that motivation is a core deficit in ADHD such that youth with ADHD experience difficulties initiating and sustaining motivation, which leads to poor academic functioning. Empirical evidence supports the presence of general motivation deficits in children with ADHD that are connected to low academic achievement, although this remains understudied in adolescents with ADHD, including the influence of sex on motivation despite well-documented differences in motivation by sex in typically developing students (see Smith & Langberg, 2018).

Several studies examined motivation among middle school students with ADHD. Although not utilizing measures of motivation consistent with the EVC model or achievement goal theory, Smith et al. (2020) found that eighth grade students with ADHD reported higher levels of maladaptive motivation compared to students without ADHD. For students with ADHD, high levels of maladaptive motivation were associated with poor homework performance and low math fluency. Students with ADHD who reported high levels of adaptive motivation experienced higher reading accuracy. These results suggest that students with ADHD who experience high levels of adaptive motivation may aid achievement, even if they report lower levels of motivation compared to their non-ADHD peers.

Barron et al. (2006) examined achievement goals of sixth grade students with and without ADHD and the association between achievement goals and GPA over one school year. Results indicated students with ADHD endorsed higher levels of mastery goal orientation (i.e., acquiring skills for competence) relative to performance-approach goal orientation (i.e., appearing to perform the best) and performance-avoidance (i.e., avoiding performing the worst). They also endorsed lower levels of performance-approach goal orientation relative to performance-avoidance. Compared to students without ADHD, students with ADHD endorsed lower levels of performance approach. When examining associations between achievement goals and GPA over the school year for students with ADHD, results of regression models revealed that performance avoidance positively predicted GPA at the end of the school year, such that students with ADHD who reported higher levels of performance avoidance achieved higher GPAs. These results may give credence to the idea that some level of motivation to achieve, regardless of the motive behind it, may enhance achievement. However, performance avoidance was associated with maladaptive academic behaviors, too. Mastery predicted both adaptive academic behaviors and maladaptive academic behaviors but was not associated with GPA. These findings highlight the relative advantages of both mastery and performance-avoidance goals in predicting achievement.

Research has also examined expectancy (i.e., belief in ability to be successful) and value (i.e., intrinsic interest) constructs among adolescents with ADHD. Langberg et al. (2018) examined homework motivation among middle school students with ADHD. Results indicated that, after accounting for ADHD symptoms and math achievement, expectancy significantly predicted parent-reported homework problems and engagement in behaviors consistent with homework completion, but value did not. By teacher-report, the model indicated that expectancy and value predicted engagement in behaviors that aided homework completion. Expectancy also predicted teacher-reported homework completion, but value did not. Moreover, when examining teacher-reported homework outcomes, ADHD symptoms were not significant predictors, indicating motivation and achievement may eclipse ADHD symptoms in this aspect of academic functioning. However, this study did not evaluate ADHD symptoms dimensionally to understand differences in expectancy and value effects on homework by ADHD symptom levels. They also did not consider cost (i.e., negative factors associated with achieving). These findings nevertheless support an association between expectancy and value with facets of achievement.

A few studies have examined motivation among high school-aged adolescents with ADHD, although motivation is not conceptualized according to the EVC model or achievement goal theory. Birchwood and Daly (2012) examined the association between intrinsic motivation (similar to the value construct) for school and exam scores among 15- and 16-year-old students who self-reported symptoms of ADHD. Both ADHD symptoms and motivation were significantly associated with exam scores. Sibley et al. (2019) examined differences in academic interest and value of academic outcomes among a small sample of ninth grade students with and without ADHD. Results indicated adolescents with ADHD reported lower levels of value of academic outcomes and marginally significantly lower levels of academic interest compared to those without ADHD. However, they did not find associations between motivation and GPA.

Together, findings extend the literature supporting motivation deficits among children with ADHD to adolescents with ADHD and the association of adaptive and maladaptive levels of motivation to academic achievement. However, there is a need to examine additional theory-based conceptualizations of motivation in a variety of academic contexts among older adolescents with ADHD. The lack of an association between motivation and GPA suggests that associations between motivation and achievement varies among older students compared to younger students. Alternatively, it may be that certain motivation constructs operate differently in their associations with achievement based on ADHD symptom levels.

Motivation may be particularly important for adolescents, as they are expected to take on greater independence managing academic demands that influence future functioning. These expectations are heightened for students who are college-bound. Students with ADHD generally experience academic impairment compared to students without ADHD (Fischer et al., 1993) and frequently fail at academic tasks (DuPaul & Langberg, 2014) that can lead to low expectancies of success and judgments of competence (Olivier & Steenkamp, 2004). Thus, high school-aged adolescents with elevated ADHD symptoms may be particularly plagued by low motivation given accumulated experiences of academic difficulties. Nevertheless, college-bound students with ADHD exhibit sufficient academic skills to attend college and may learn ways to harness motivation such that motivation constructs operate differently for predicting achievement compared to their peers. Additionally, these youth choose to continue schooling when not required after high school and despite financial cost, suggesting unique motivational aspects of these youth. At the same time, evidence suggests that youth with ADHD histories who attend college still perform poorer than their peers without ADHD histories (Burr et al., 2022). Understanding motivation among college-bound youth with elevated ADHD symptoms and its connection to achievement may help to prevent poor academic trajectories (see Burr et al., 2022; Kent et al., 2011) by indicating areas where intervention may be implemented to enhance motivation and academic functioning. In addition, students’ motivation (Jacobs et al., 2002) and academic achievement (Burr et al., 2022) typically decrease over schooling (Jacobs et al., 2002). Thus, anticipating this downward trajectory among college-bound adolescents with elevated ADHD symptoms and how it affects achievement, while also acknowledging that students who attend college have high levels of motivation, may have important implications for intervention.

Current Study

The purpose of the current study was to examine academic motivation according to achievement goal theory and the EVC model during high school using retrospective report of college students with varying levels of ADHD symptoms. To accomplish this, we gathered retrospective self-report data from first-year college students about their academic motivation and GPA during their senior year of high school. We had the following aims: (1) describe the achievement goals and EVC levels and their relationships to ADHD symptoms among college students retrospectively reporting on their final year of high school, (2) evaluate the relationships between achievement goals and EVC levels to academic functioning, and (3) evaluate whether these relationships are moderated by ADHD symptom level. Based on previous findings and developmental considerations, it was expected that students with high levels of ADHD symptoms would report lower levels of adaptive motivation (i.e., mastery, performance-approach, expectancy, and value) and higher levels of maladaptive motivation (i.e., performance-avoidance and cost) in their senior year of high school relative to students with low symptoms. It was hypothesized that adaptive motivation would be positively associated with GPA and that maladaptive motivation would be negatively associated with GPA. Given the dearth of studies examining differences in the association between theory-driven models of motivation and GPA among college-bound adolescents with ADHD, no hypotheses were made regarding moderating effects of motivation constructs in the association between GPA by ADHD symptom levels.

Method

Participants

Participants were 461 first year undergraduates at a state university in the Midwest recruited in the 2019 to 2020 academic year as part of an online participant pool for students enrolled in psychology courses. Participants were 18- (64.0%) or 19-years-old, and most were female (73.8%). This proportion of females is consistent with the proportion of females among the 2019 to 2020 incoming first year students (70% female) at the university. All participants were at most 1 year removed from high school. Approximately 12% completed the survey at 3 months after high school graduation, 42% completed the survey 4 to 6 months after high school graduation, 23% completed the survey 7 to 9 months after high school graduation, and 22% completed the survey 10 to 12 months after high school graduation. Information about participants’ racial and ethnic background was not available. However, during the 2019 academic year, first year students enrolled in the College, from which this sample was recruited, were predominantly White (81.4%), followed by Black or African American (5.9%), Biracial or Multiracial (5.6%), Hispanic or Latinx (race not specified; 4.7%), Asian or Asian American (2.1%), and American Indian/Alaska Native (0.2%). Participants reported their parents’ total household income (7.4% below $50,000, 26.2% between $50,000 and $99,999, and 39.3% above $100,000) and 27.1% reported not knowing their total household income or preferred to not answer. Information about participants’ previous ADHD diagnostic histories was not reported.

Procedures

Research procedures were approved by the university’s Institutional Review Board. Participants were recruited for the current study from the university’s psychology participant pool. Individuals who were 18-years-old or older, consented to participate and completed an online survey using the Research Electronic Data Capture (REDCap) system (Harris et al., 2009). Students were asked to complete measures of motivation based on their 12th grade English class to capture motivation to engage in relatively similar academic tasks that all participants would have taken and to capture a specific rather than global measure of motivation, as motivation varies across subjects (see Smith & Langberg, 2018). Data were included in the current study if students provided complete data for all study measures, were 18- or 19-years-old, and took an English class in 12th grade. In addition, as the effect of sex was controlled for in the analyses in line with arguments for examining the importance of sex differences in motivation (see Smith & Langberg, 2018), participants who described their sex as neither male nor female (n = 1) or preferred not to answer (n = 1) were not included in the current study due to inadequate power to account for group differences.

Measures

ADHD Symptoms

Participants completed the World Health Organization Adult ADHD self-report scale (ASRS-v1.1) Screener (Kessler et al., 2007) to measure ADHD symptoms. The ASRS-v1.1 is a 6-item self-report screener that asks participants to rate how often they experienced six inattentive and hyperactive/impulsive symptoms of ADHD in the past 6 months from “never” (0) to “very often” (4). Individual symptom ratings are considered elevated if participants endorse “sometimes,” “often,” or “very often” for the first three items and if they endorse “often” or “very often” for the last three items. The number of elevated symptoms ranging from zero to six was used as a measure of ADHD symptoms for the current study. The ASRS-v1.1 Screener has been validated among adults 18-years-old and older for its ability to identify those at risk for ADHD, and the 6-item screener has been found to be most predictive of ADHD compared to 18-item Adult ADHD Self-Report Scale (Kessler et al., 2007). Among college students, the ASRS screener has been found to demonstrate concurrent validity with the Conners Adult ADHD Rating Scale (CAARS) long self-report form (Conners et al., 1999; Lovett et al., 2021), suggesting the utility of the ASRS screener for measuring ADHD symptoms. Internal consistency was fair in the current sample (α = .76).

Academic Motivation

Participants completed the Patterns of Adaptive Learning Scales (PALS; Midgley et al., 2000) Student Scales, Personal Achievement Goal Orientations Scales (Revised). The PALS consists of 14 items and measures students’ self-reported academic motivation in three goal orientation scales: mastery (five items), performance approach (five items), and performance-avoidance (four items). Students rate how true a series of statements are from “1” meaning “not at all true” to “5” meaning “very true.” Factor analyses provide support for the construct validity of the scales (Midgley et al., 2000) and higher scores on each scale reflect greater alignment with the achievement goal. To capture domain-specific motivation in a consistent context rather than averaging motivation across all subjects where motivation varies and to ensure that participants were rating motivation to engage in relatively similar academic tasks (see Smith & Langberg, 2018), participants in the current study were asked to complete the PALS based upon their experience in their 12th grade English class. Internal consistency was excellent for the mastery (α = .92) and performance approach (α = .92) scales and was good for the performance avoidance scale (α = .87).

Participants completed the Expectancy-Value-Cost (EVC) Scale (Kosovich et al., 2015), which is a 10-item self-report measure of students’ motivation to achieve academically in a class. Respondents rated how strongly they disagreed (“1”) or agreed (“6”) with a series of statements describing the perceived expectancy, value, and cost associated with achieving in their 12th grade English class. Students’ 12th grade English class was chosen to ensure that students were rating motivation to engage in tasks that would be consistent across contexts, to capture domain-specific motivation due to motivation varying across academic subjects (see Smith & Langberg, 2018), and to measure this domain-specific motivation in a class that all students would have taken in their last year of high school. The EVC Scale produces three separate domain scores: expectancy (three items), value (three items), and cost (four items). Higher scores in each domain reflect greater endorsement of expectancy, value, and cost. Evidence of internal consistency, test-retest reliability, and construct, convergent, and discriminant validity of the EVC Scale are favorable in a young adolescent sample (Kosovich et al., 2015). In the current sample, internal consistency was excellent for the expectancy (α = .92) and value (α = .91) subscales and fair for the cost subscale (α = .76).

Academic Achievement

Participants’ self-reported high school GPA at graduation was used as a measure of academic achievement. A weighted GPA was used such that GPA could range from 0.0, reflecting low achievement, to 5.0, reflecting high achievement.

Data Analytic Plan

To assess Aim 1, descriptive statistics were calculated to characterize participants’ endorsement of mastery, performance approach, and performance avoidance goal orientations and levels of expectancy, value, and cost during 12th grade. Bivariate correlations were also calculated between achievement goal orientation levels, EVC levels, and GPA to examine associations among study variables. Then, a multivariate linear regression model was used to examine which achievement goal orientations and/or EVC levels accounted for a significant amount of variance in GPA, controlling for the effects of sex (Aim 2). We controlled for the effects of sex due to empirically-documented differences in motivation between males and females (see Smith & Langberg, 2018). Finally, interaction effects were calculated between ADHD symptom levels and motivation measure variables. Study variables included in the calculation of interaction effects were first mean-centered to aid the meaningful interpretation of regression coefficients (Hayes, 2018). Then, interaction effects were included in hierarchical multivariate linear regression models to examine the moderating effects of ADHD symptoms on the association between academic motivation constructs and GPA (Aim 3). For significant interaction effects, the Johnson-Neyman (JN) technique was employed using the PROCESS macro in SPSS (Hayes, 2018) to probe at what level of ADHD symptoms the association between academic motivation constructs and GPA was statistically significant.

Results

Aim 1

The first aim of the study was to describe the achievement goals and EVC levels of the participants and their relationships to ADHD symptoms. Descriptive statistics for the sample are displayed in Table 2. These findings indicate that participants endorsed high levels of expectancy, moderately low levels of cost, and moderate levels of mastery, performance approach, and performance avoidance. Examining associations between motivation constructs and ADHD symptoms using bivariate correlations revealed small significant associations between ADHD symptom levels and expectancy, value, cost, mastery, and performance avoidance in the expected directions (see Table 2). Performance approach was not significantly correlated with ADHD symptom levels.

Table 2.

Correlations Among Study Variables and Descriptive Statistics.

	1	2	3	4	5	6	7	8
1. Sex
2. Number of elevated ADHD symptoms	−.09
3. EVC expectancy	.06	−.20**
4. EVC value	.11*	−.18**	.43**
5. EVC cost	−.15*	.26**	−.29**	−.13*
6. PALS mastery	.07	−.26**	.21**	.36**	−.14*
7. PALS performance approach	−.08	.02	.09*	.07	.07	.27**
8. PALS performance avoidance	.04	.14*	.05	.01	.08	.14*	.63**
9. GPA at high school graduation	.22**	−.13*	.13*	.05	−.13*	.22**	.13*	.10*
M (SD) /%	73.8% female	2.52 (1.79)	5.19 (0.86)	4.34 (1.23)	2.82 (0.95)	3.37 (0.99)	2.73 (1.08)	3.05 (1.03)

Note. Sex coded as 0 = male, 1 = female. Participants were either 18 or 19-years-old and male or female. Number of elevated ADHD symptoms ranged from 0 to 6, with elevated symptoms of 4 or more indicating a risk for ADHD. EVC Scale scores range from 1 to 6, with higher scores indicating higher levels of expectancy, value, or cost. PALS scores range from 1 to 5, with higher scores indicating greater goal orientation alignment.

p < .05. **p < .001.

Aim 2

To evaluate the relationships between achievement goals and EVC levels to academic functioning, bivariate correlations were calculated among study variables included in the multivariate linear regression models (i.e., achievement goals and EVC variables). Associations among motivation variables revealed some significant small correlations between motivation constructs (significant rs range: −.29 between expectancy and cost to .36 between value and mastery; all ps < .05). Notably, there was a significant moderate positive correlation between performance approach and performance avoidance (r = .63, p < .001). There was a small positive correlation between GPA at high school graduation and expectancy, mastery, performance approach, and performance avoidance (rs range: .10–.22, all ps < .05) and a small negative correlation between GPA and cost (r = −.13, p = .005). Value was not significantly associated with GPA.

We then analyzed the relationship between motivation constructs and high school GPA in a multiple linear regression model, controlling for the effects of sex. After accounting for sex, all motivation constructs jointly accounted for a significant amount of variance in GPA (R² = .12, F(7, 453) = 8.49, p < .001). In the presence of all motivation constructs, only mastery accounted for a significant amount of variance in GPA (β = .18, p < .001), and performance approach accounted for a marginally significant amount of variance in GPA (β = .10, p = .081; see Table 3 for results). Collinearity statistics revealed no concerns for multicollinearity (all tolerance values range: 0.56–0.90; variance inflation factor values range: 1.06–1.80).

Table 3.

Summary of Regression Analysis for Predicting GPA (N = 461).

	Variable	β	SE β	F	ΔF	ΔR ²
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97***
Step 2					5.66	0.07
	EVC expectancy	.08	.02	2.55
	EVC value	−.09	.02	2.70
	EVC cost	−.07	.02	2.21
	PALS mastery	.18	.02	13.37***
	PALS performance approach	.10	.02	3.06*
	PALS performance avoidance	.00	.02	0.00
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97***
Step 2					5.17	0.02
	Expectancy	.09	.02	4.11**
	ADHD symptoms	−.10	.01	4.22**
Step 3					0.59	0.00
Step 3	Expectancy × ADHD symptoms	.04	.01	0.59
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97***
Step 2					3.13	0.01
	Value	.01	.02	0.06
	ADHD symptoms	−.11	.01	5.79**
Step 3					2.25	0.01
Step 3	Value × ADHD symptoms	.07	.01	2.25
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97***
Step 2					4.42	0.02
	Cost	−.08	.02	2.61
	ADHD symptoms	−.09	.01	4.08**
Step 3					0.57	0.00
Step 3	Cost × ADHD symptoms	−.03	.01	0.57
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97***
Step 2					11.59	0.05
	Mastery	.19	.02	16.77***
	ADHD symptoms	−.07	.01	2.01
Step 3					5.13	0.01
Step 3	Mastery × ADHD symptoms	.10	.01	5.13**
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97***
Step 2					9.05	0.04
	Performance approach	.15	.02	11.75**
	ADHD symptoms	−.12	.01	6.51**
Step 3					3.71	0.01
Step 3	Performance approach × ADHD symptoms	.09	.01	3.71*
Step 1					23.97	0.05
Step 1	Sex	.22	.04	23.97**
Step 2					6.11	0.03
	Performance avoidance	.11	.02	5.96**
	ADHD symptoms	−.13	.01	8.02**
Step 3					1.90	0.00
Step 3	Performance avoidance × ADHD symptoms	.06	.01	1.90

Note. Sex coded as 0 = male, 1 = female.

p < .10. **p < .05. ***p < .001.

Aim 3

A series of hierarchical linear regression models were used to examine the moderating effects of ADHD symptom levels on all motivation constructs in separate regression models, controlling for the effects of sex. Table 3 presents the results of these analyses. Only the interaction between mastery scores and ADHD symptoms was significantly associated with GPA (β = .10, p = .024), indicating that at high ADHD symptom levels (i.e., one standard deviation above the mean), higher levels of mastery were associated with higher GPA relative to when ADHD symptoms are high and mastery is lower. When ADHD symptoms are low (i.e., one standard deviation below the mean) and mastery is high, GPA is lower relative to when ADHD symptoms are high (i.e., one standard deviation above the mean) and mastery is high. Results of analyses using the JN technique revealed that at low levels of ADHD symptoms (i.e., at and below a mean-centered score of −1.32; approximately one standard deviation below the sample mean), the conditional effects of mastery are not significantly associated with GPA (ps ≥ .05). However, above this threshold, the conditional effects of mastery are significantly associated with GPA (all ps < .05).

Discussion

The current study examined the motivation of college students with varying levels of ADHD symptoms retrospectively reporting on their academic achievement and motivation according to achievement goal theory and the EVC model during their last year of high school. Generally consistent with hypotheses, students endorsing more elevated symptoms of ADHD reported lower levels of adaptive motivation (i.e., expectancy, value, and mastery) and higher levels of maladaptive motivation (i.e., cost and performance avoidance), compared to students with fewer ADHD symptoms. When examining the association between motivation constructs and GPA at high school graduation, hypotheses were not entirely supported. Expectancy, mastery, performance approach, and cost were associated with GPA in the expected directions. However, performance avoidance was positively correlated with GPA, and there was no significant association between value and GPA. When considered together and after accounting for sex, all motivation constructs accounted for significant variance in GPA, but only mastery exerted unique significant positive effects on GPA. Similarly, there were significant moderating effects of ADHD symptom levels on the association between mastery and GPA, but not for other motivation constructs.

Motivation Levels and ADHD Symptoms

Examining associations between motivation constructs retrospectively reported in students’ last year of high school and ADHD symptom levels demonstrated that higher levels of ADHD symptoms were generally associated with lower levels of retrospectively reported adaptive motivation (rs range: −.18 to −.26) and higher levels of retrospectively reported maladaptive motivation (rs range: .14–.26). Overall, these findings are consistent with deficits of motivation highlighted among children with ADHD (Smith & Langberg, 2018) and are consistent with findings that middle school-aged adolescents with ADHD endorse higher levels of maladaptive motivation and lower levels of adaptive motivation relative to non-ADHD peers (Smith et al., 2020). It is reasonable to expect that these deficits may increase over time for college-bound adolescents with elevated ADHD symptoms, particularly as repeated experiences of academic difficulties may lead to lower adaptive and higher maladaptive motivation for those adolescents. Of note, in the current study performance approach motivation was not correlated with ADHD symptom levels. This finding is not consistent with the findings of Barron et al. (2006) who found that middle school-aged adolescents with ADHD endorsed higher levels of performance approach relative to non-ADHD peers. It may be that by high school age and for students who enter college, increasingly realistic self-appraisals and associated social pressures lead adolescents with ADHD to reconsider a competitive approach.

Associations Between Motivation and Academic Achievement

Retrospectively reported expectancy, mastery, performance approach, and performance avoidance were positively associated with GPA, while cost was negatively associated with GPA. There was no significant association between value and GPA. Considered together and after accounting for sex, all motivation constructs accounted for significant variance in GPA, but only mastery accounted for significant variance in GPA such that higher levels of mastery were associated with higher GPA relative to lower levels of mastery.

These findings are generally consistent with those of Smith et al. (2020) and Langberg et al. (2018) implicating associations between adaptive motivation and achievement and associations between maladaptive motivation and academic problems. Also, these findings replicate those of Barron et al. (2006) who found a positive association between performance avoidance and GPA in middle school students with ADHD. Given the positive association between performance avoidance and GPA, it may be that this goal orientation is adaptive for older students with symptoms of ADHD who enter college. It may be that these students, who typically perform poorer than peers with fewer ADHD symptoms (see Fischer et al., 1993), benefit from a motivational orientation whereby they use peers’ performance as a benchmark for avoiding poor performance. However, given this weak association in correlational analyses and the lack of evidence supporting the unique significant effects of performance avoidance in regression models, firm conclusions should not be made until these findings are replicated in other studies.

The null findings regarding the association between value and GPA are consistent with theory and evidence suggesting value has stronger associations with interest outcomes (e.g., interest in learning about academic subjects) than performance outcomes (e.g., test scores; see Barron & Hulleman, 2014) and with findings in a young sample of high school-aged adolescents with ADHD (Sibley et al., 2019). Nevertheless, this finding is inconsistent with evidence suggesting a weak association between value and performance outcomes in middle school students with ADHD (Langberg et al., 2018). As suggested by Sibley et al. (2019), null findings regarding the association between value and GPA in the current study may be explained by declines in interest during high school (Gottfried et al., 2001). The current study asked college students to retrospectively report motivation and GPA at the end of high school when interest would be expected to be low relative to the beginning of high school when Sibley et al. (2019) measured motivation and achievement.

The unique association of mastery with GPA lends support to the mastery goal perspective (Ames, 1992). However, the trend supporting a unique association between performance approach and GPA lends some support to the benefits of espousing multiple goal orientations (see Barron & Harackiewicz, 2001; Harackiewicz et al., 2002). These findings also suggest the relative utility of achievement goal theory over the EVC model in that only mastery was associated with GPA. However, the effects of mastery were small (β = 0.18), calling into question the meaningfulness of this finding. Yet, even a small effect of mastery on GPA are notable given the myriad other influences on achievement, highlighting the importance of future research in this area.

Moderating Effects of ADHD

ADHD symptom levels significantly moderated the association between mastery and GPA such that high levels of ADHD symptoms paired with high levels of mastery (relative to others in this sample) were associated with high GPA. It is important to note that this moderating effect was only present when ADHD symptoms were not low. In other words, when students had moderate to high levels of ADHD symptoms (i.e., 1 SD above the mean in the current sample), having high levels of mastery goal orientation was associated with a high GPA. This suggests that mastery exerts beneficial effects on GPA at average and above levels of ADHD symptoms but does not exert the same beneficial effects at lower levels of ADHD symptoms.

These findings are consistent with work in support of the mastery goal perspective (Ames, 1992) and extend support for this perspective among college students with ADHD symptoms retrospectively reporting their motivation and achievement at the end of high school. In addition, these results are generally consistent with Smith et al. (2020) who found that middle school-aged adolescents with ADHD who endorsed high levels of adaptive motivation experienced higher GPA and reading accuracy relative to low levels of adaptive motivation. In their sample, Barron et al. (2006) found that mastery was associated with academic self-efficacy but not GPA. It may be that the effects of mastery exert positive effects on GPA for college-bound students with ADHD through enhanced self-efficacy, which is associated with academic effort (Newark et al., 2016) that is required for success as difficulty of coursework and expectations increase during high school.

Findings suggesting increased benefits of high levels of mastery on GPA for college-bound students with more ADHD symptoms compared to students with fewer ADHD symptoms are novel. This finding could be unique to college-bound students with elevated ADHD symptoms, who, even if experiencing elevated symptoms of ADHD, adequately achieved to gain admission to a university. In addition, it may be that for youth with low levels of ADHD symptoms, mastery is not as necessary to do well academically, dampening this association. However, for students with academic impairment related to ADHD, mastery may be important to facilitate achievement, accounting for the moderating effect found in this study. These findings of the benefits of mastery support motivation as a factor promoting resilience for youth with elevated ADHD symptoms. These results suggest mastery may be a protective factor for academic functioning in college-bound youth with elevated ADHD symptoms.

Limitations and Future Directions

Results of this study must be interpreted considering its limitations. First, this study relied on retrospective self-report of motivation and ADHD symptoms. The current sample was restricted to students in their first year of college, about half of whom (54%) completed the survey within 6 months after high school graduation, and who were at most one school year removed from their senior year of high school. It is possible that students’ present experience of motivation influenced their retrospective report of motivation, despite question anchors instructing participants to complete ratings for their 12th grade English class. The validity of self-report should be enhanced in future studies that use self-report during high school and that use longitudinal study designs. This study relied on cross-sectional data, which limited the ability to make causal interpretations about associations between motivation and achievement. In addition, the study sample was a convenience sample not composed of individuals with diagnosed ADHD. Some participants may have ADHD diagnoses or histories, but this data was unavailable for the current study. In addition, information about participants’ race was not available for this study, so the racial representativeness of the sample and generalizability cannot be evaluated. The current study relied entirely on self-report data, which may have enhanced the magnitude of associations among study variables. Longitudinal studies of motivation among adolescents with ADHD are needed to better understand relationships among motivation constructs and academic achievement (see Smith & Langberg, 2018), including bidirectional effects between academic achievement and motivation constructs (Kosovich et al., 2017). Results from this study should be considered preliminary and in need of replication with samples of clinically diagnosed high school-aged adolescents using measures from multiple informants collected longitudinally. Future research should examine how patterns of motivation constructs (see Conley, 2012) are associated with academic achievement among adolescents with ADHD to be consistent with current conceptualizations of adaptive motivation (Hulleman et al., 2008).

Clinical Implications

Interventions designed to improve class-wide motivation have already shown positive results (see Hulleman & Harackiewicz, 2009). There are also interventions that may be promising to enhance motivation according to achievement goal theory and the EVC model. For example, growth mindset (Martin, 2013) interventions may enhance students’ expectancy (Kosovich et al., 2015), and motivational interviewing may enhance motivation (Sibley et al., 2016) to increase value associated with achievement, which may also enhance mastery (Jiang et al., 2018). Results from the current study suggest these interventions that enhance mastery may be particularly beneficial for college-bound adolescents with moderate to high levels of ADHD symptoms. Mental health professionals may find the greatest gains in motivation and therefore achievement among these students by attempting to enhance students’ sense of mastery of academic material and skills. There may also be benefits to motivation inherent in interventions that improve the academic functioning of adolescents with elevated ADHD symptoms. For example, multi-component skills training interventions that have been shown to improve the academic functioning of middle (Evans et al., 2016) and high school students with ADHD (DuPaul et al., 2021) may enhance motivation by increasing expectancy of success, decreasing cost associated with achieving, and increasing mastery by equipping students with skills to achieve. The role of motivation in these interventions represent an area ripe for research to better understand intervention effects and improve functioning.

Conclusion

This study builds upon prominent motivation theories and extends these theories to understand motivation among college-bound high school-aged students with elevated ADHD symptoms. In addition, this study extends evidence indicating motivation deficits in children and young adolescents with ADHD associated with academic achievement to college-bound adolescents with elevated ADHD symptoms. Although there were not differential associations between all motivation constructs and academic achievement by ADHD symptom levels, the results of the current study suggest mastery may exert beneficial effects on achievement for college-bound high school students with elevated ADHD symptoms. The results of this study highlight the importance of rigorously examining motivation according to achievement goal theory and the EVC model and its association with academic achievement during high school among adolescents with ADHD. Future study of these important relationships is necessary to understand the relationship between motivation and academic functioning and ultimately benefit college-bound adolescents with elevated ADHD symptoms through intervention development.

Footnotes

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

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

R. Elizabeth Capps

Steven W. Evans

Author Biographies

R. Elizabeth Capps, MA, is a doctoral student in Clinical Psychology at Ohio University. Her research interests focus on understanding the academic and social functioning of adolescents with ADHD and school-based intervention development and evaluation for adolescents with ADHD and co-occurring concerns.

Steven W. Evans is a distinguished professor at Ohio University in the Department of Psychology. He is the co-director of the Center for Intervention Research in Schools. His research interests are within school mental health broadly, and specifically focused on treatment development and evaluation research for adolescents with attention-deficit/hyperactivity disorder and related problems.

Mary Lee Shea, MS, is a doctoral student in Clinical Psychology at Ohio University. Her research interests focus on exploring how to best support students, including supporting teachers in using high quality interventions.

References

Ames

(1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261–271.

Barkley

R. A.

(1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94.

Barron

K. E.

Evans

S. W.

Baranik

L. E.

Serpell

Z. N.

Buvinger

(2006). Achievement goals of students with ADHD. Learning Disability Quarterly, 29, 1–22.

Barron

K. E.

Harackiewicz

J. M.

(2001). Achievement goals and optimal motivation: Testing multiple goal models. Journal of Personality and Social Psychology, 80, 706–722.

Barron

K. E.

Hulleman

C. S.

(2014). Expectancy-value-cost model of motivation. In Eccles

J. S.

Salmelo-Aro

(Eds.), International encyclopedia of social and behavioral sciences. Motivational psychology (2nd ed., pp. 503–509). Elsvier.

Birchwood

Daley

(2012). The impact of Attention Deficit Hyperactivity Disorder (ADHD) symptoms on academic performance in an adolescent community sample. Journal of Adolescence, 35, 225–231.

Burr

S. M. D. L.

Lefebre

J-A.

Arnold

L. E.

Epstein

J. N.

Hinshaw

S. P.

Molina

B. S. G.

Hechtman

Hoza

Jensen

P. S.

Vitiello

Pelham

W. E.

Jr. Howard

A. L.

(2022). Paths to postsecondary education enrollment among adolescents with and without childhood attention-deficit/hyperactivity disorder (ADHD): A longitudinal analysis of symptom and academic trajectories. Child Development, 93(5), e563–e580.

Conley

A. M.

(2012). Patterns of motivation beliefs: Combining achievement goal and expectancy-value perspectives. Journal of Educational Psychology, 104, 32–47.

Conners

C. K.

Erhardt

Sparrow

(1999). Conners’ adult ADHD rating scales. Multi-Health Systems.

10.

DuPaul

G. J.

Evans

S. W.

Owens

J. S.

Cleminshaw

C. L.

Kipperman

K. L.

Benson

(2021). School-based intervention for adolescents with attention-deficit/hyperactivity disorder: Effects on academic functioning. Journal of School Psychology, 87, 48–63.

11.

DuPaul

G. J.

Langberg

J. M.

(2014). Educational impairments in children with ADHD. In Barkley

R. A.

(Ed.), Attention-deficit/hyperactivity disorder: A handbook for diagnosis and treatment (4th ed., pp. 169–190). Guilford Press.

12.

Dweck

C. S.

(1986). Motivational processes affecting learning. American Psychologist, 41, 1040–1048.

13.

Eccles

J. S.

(2005). Subjective task value and the Eccles et al. model of achievement-related choices. In Elliot

A. J.

Dweck

C. S.

(Eds.), Handbook of competence and motivation (pp. 105–121). Guilford.

14.

Eccles

J. S.

Vida

M. N.

Barber

(2004). The relation of early adolescents’ college plans and both academic ability and task-value beliefs to subsequent college enrollment. The Journal of Early Adolescence, 24, 63–77.

15.

Eccles

J. S.

Wigfield

(1995). In the mind of the actor: The structure of adolescents’ achievement task values and expectancy-related beliefs. Personality and Social Psychology Bulletin, 21, 215–225.

16.

Eccles

J. S.

Wigfield

Schiefele

(1998). Motivation to succeed. In Damon

Eisenberg

(Eds.), Handbook of child psychology: Social, emotional, and personality development (p. 1017–1095). John Wiley & Sons, Inc.

17.

Elliot

A. J.

Church

M. A.

(1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72, 218–232.

18.

Evans

S. W.

Langberg

J. M.

Schultz

B. K.

Vaughn

Altaye

Marshall

S. A.

Zoromski

A. K.

(2016). Evaluation of a school-based treatment program for young adolescents with ADHD. Journal of Consulting and Clinical Psychology, 84, 15–30.

19.

Fischer

Barkley

R. A.

Fletcher

K. E.

Smallish

(1993). The adolescent outcome of hyperactive children: Predictors of psychiatric, academic, social, and emotional adjustment. Journal of the American Academy of Child & Adolescent Psychiatry, 32, 324–332.

20.

Gottfried

A. E.

Fleming

J. S.

Gottfried

A. W.

(2001). Continuity of academic intrinsic motivation from childhood through late adolescence: A longitudinal study. Journal of Educational Psychology, 93, 3–13.

21.

Harackiewicz

J. M.

Barron

K. E.

Pintrich

P. R.

Elliot

A. J.

Thrash

T. M.

(2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94, 638–645.

22.

Harris

P. A.

Taylor

Thielke

Payne

Gonzalez

Conde

J. G.

(2009). Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42, 377–381.

23.

Hayes

A. F.

(2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). The Guilford Press.

24.

Hulleman

C. S.

Durik

Schweigert

Harackiewicz

(2008). Task values, achievement goals, and interest: An integrative analysis. Journal of Educational Psychology, 100, 398–416.

25.

Hulleman

C. S.

Harackiewicz

J. M.

(2009). Promoting interest and performance in high school science classes. Science, 326, 1410–1412.

26.

Jacobs

J. E.

Lanza

Osgood

D. W.

Eccles

Wigfield

(2002). Changes in children’s self-competence and values: Gender and domain differences across grades one through twelve. Child Development, 73, 509–527.

27.

Jiang

Rosenzweig

E. Q.

Gaspard

(2018). An expectancy-value-cost approach in predicting adolescent students’ academic motivation and achievement. Contemporary Educational Psychology, 54, 139–152.

28.

Kent

K. M.

Pelham

W. E.

Molina

B. S.

Sibley

M. H.

Waschbusch

D. A.

Gnagy

E. M.

Biswas

Babinski

D. E.

Karch

K. M.

(2011). The academic experience of male high school students with ADHD. Journal of Abnormal Child Psychology, 39, 451–462.

29.

Kessler

R. C.

Adler

L. A.

Gruber

M. J.

Sarawate

C. A.

Spencer

Van Brunt

D. L.

(2007). Validity of the World Health Organization Adult ADHD Self-Report Scale (ASRS) Screener in a representative sample of health plan members. International Journal of Methods in Psychiatric Research, 16, 52–65.

30.

Kosovich

J. J.

Flake

J. K.

Hulleman

C. S.

(2017). Short-term motivation trajectories: A parallel process model of expectancy-value. Contemporary Educational Psychology, 49, 130–139.

31.

Kosovich

J. J.

Hulleman

C. S.

Barron

K. E.

Getty

(2015). A practical measure of student motivation: Establishing validity evidence for the Expectancy-Value-Cost Scale in middle school. Journal of Early Adolescence, 35, 790–816.

32.

Langberg

J. M.

Smith

Dvorsky

Molitor

Bourchtein

Eddy

Eadeh

Oddo

(2018). Factor structure and predictive validity of a homework motivation measure for use with middle school students with attention-deficit/hyperactivity disorder (ADHD). School Psychology Quarterly, 33, 390–398.

33.

Lovett

B. J.

Ferrier

D. E.

Wang

Jordan

A. H.

(2021). Adult ADHD Self-Report Scale Screener ratings in college students: Concurrent validity and test–retest reliability. Journal of Psychoeducational Assessment, 39, 1015–1019.

34.

Martin

(2013). Improving the achievement, motivation, and engagement of students with ADHD: The role of personal best goals and other growth-based approaches. Australian Journal of Guidance and Counseling, 23, 143–155.

35.

Meece

J. L.

Glienke

B. B.

Burg

(2006). Gender and motivation. Journal of School Psychology, 44, 351–373.

36.

Midgley

Maehr

Hruda

Anderman

Freeman

Gheen

Kaplan

Kumar

Middleton

Nelson

Roeser

Urdan

Tim

. (2000). The Patterns of Adaptive Learning Scales (PALS). The University of Michigan.

37.

Newark

P. E.

Elsässer

Stieglitz

R. D.

(2016). Self-esteem, self-efficacy, and resources in adults with ADHD. Journal of Attention Disorders, 20, 279–290.

38.

Nicholls

J. G.

(1979). Quality and equality in intellectual development: The role of motivation in education. American Psychologist, 34, 1071–1084.

39.

Olivier

M. A.

Steenkamp

D. S.

(2004). Attention-deficit/hyperactivity disorder: Underlying deficits in achievement motivation. International Journal for the Advancement of Counselling, 26, 47–63.

40.

Sibley

M. H.

Graziano

P. A.

Kuriyan

A. B.

Cox

Pelham

W. E.

Rodriguez

Sanchez

Derefinko

Helseth

Ward

(2016). Parent-teen behavior therapy + motivational interviewing for adolescents with ADHD. Journal of Consulting and Clinical Psychology, 84, 699–712.

41.

Sibley

M. H.

Graziano

P. A.

Ortiz

Rodriguez

Coxe

(2019). Academic impairment among high school students with ADHD: The role of motivation and goal-directed executive functions. Journal of School Psychology, 77, 67–76.

42.

Simpkins

S. D.

Davis-Kean

P. E.

Eccles

J. S.

(2006). Math and science motivation: A longitudinal examination of the links between choices and beliefs. Developmental Psychology, 42, 70–83.

43.

Smith

Z. R.

Langberg

J. M.

(2018). Review of the evidence for motivation deficits in youth with ADHD and their association with functional outcomes. Clinical Child and Family Psychology Review, 21, 500–526.

44.

Smith

Z. R.

Langberg

J. M.

Cusick

C. N.

Green

C. D.

Becker

S. P.

(2020). Academic motivation deficits in adolescents with ADHD and associations with academic functioning. Journal of Abnormal Child Psychology, 48, 237–249.