Decoding Instruction improves Reading Comprehension for Struggling Readers in Grade One

Introduction

Reading instruction is often at the forefront of educational research, with research-based strategies being preferred (Browder et al., 2012; Fien et al., 2015). In 2000, the National Reading Panel outlined the science of reading instruction as “(a) vocabulary, (b) fluency, (c) comprehension, (d) phonemic awareness, and (e) phonics” (Browder et al., 2012, p. 237; National Reading Panel, 2000). In many ways, these components have always had their place in reading research, educational policies, and curriculums. However, while we have defined the components of sound reading instruction, there are still students who are failing to read at grade level and questions regarding successful reading programs for all learners. Chapman (2003) notes that “approximately 15-20% of children struggle with reading” for a variety of reasons (p. 108) and while this number varies based on population and location, it is evident that current literacy practices are not promoting success for all.

Theoretical Framework

One area of debate in the literature is whether beginning reading instruction should favor sight word or decoding strategies. Through a quantitative, linear design both a “psychological-cognitive” and “language literacy-oriented” research approach will be used to focus on word reading strategies as they relate to reading comprehension (Chapman, 2003, p. 95). Sight word reading may also be termed in the literature as visual accessing (Aaron et al., 1999; Ehri, 2005; Gough, 1993), cipher reading (Gough, 1993), and/or lexical recall of the words (Aaron et al., 1999; Ryder et al., 2007). Some researches define sight words as any word that has been repeatedly read and memorized (Ehri, 2005) and others suggest sight words are limited to irregular or high frequency words (Aaron et al., 1999). Decoding strategies are often labelled as codebreaking (Gough, 1993), phonological reading (Aaron et al., 1999; Ehri, 2005), and graphophonics and/or grapheme-phoneme blending and segmenting (Aaron et al., 1999; Ehri, 2005; Eldredge et al., 1990; Weiser et al., 2011).

For the purpose of this study, the operational definition for sight word reading will be adopted from Aaron et al. (1999): “sight word reading is accomplished by addressing the orthographic representation of words” (p. 91). Gough (1993) expands this definition; a sight word “is not ‘sounded out;’ it is not read ‘phonologically.’ Its recognition is ‘direct,’ unmediated by letter-sound correspondences… [but instead] by sight” (p. 181). Decoding strategies, in contrast, are defined as “assembling the word’s pronunciation” (Aaron et al., 1999, p. 91). For the purpose of this study, decoding strategies will be operationally defined as the use of graphophonic cues – mapping the phoneme (sound) onto the grapheme (spelled representation of the word) (Saskatchewan Curriculum, 2010) – through sounding out or blending.

Review of Literature

Within the research, decoding and sight word strategies have been found to be congruent. Aaron et al. (1999) used a sample of 167 children in Grades Two through Six and 75 college students. They looked at naming time of letters in comparison to words to determine if sight word or decoding strategies were being used. They found that a switch from decoding to sight word reading was made sometime in Grade Three or Four (Aaron et al., 1999). Not only were the strategies congruent but sight words were “built on foundations of decoding skills” (Aaron et al., 1999, p. 102-3). Aaron et al. (1999) note that “sight word reading appears to be carried out by processing all the constituent letters of the word in parallel, simultaneously… [it] relies heavily on proficient decoding” (p. 115; Eldredge et al., 1990). While beginning readers often learn their first words through “selective associations” (Gough, 1993, p. 181), such as environmental print or word visualization (Ehri, 2005), this is not considered to be sight word reading. Rather, Ehri identified four stages “pre-alphabetic (environmental print), partial alphabetic (first and final sound identification), full alphabetic (decoding all of the phonemes), and consolidated alphabetic (sight word memorization) (2005, p. 173-5) – with sight word recall following the decoding stage. Thus, it can be theorized that students will be successful sight word readers if they are already successful decoders (Aaron, 1999; Uhry et al., 1997).

In Freebody’s and Byrne’s (1988) study they compared sight word and decoding strategies through regular, irregular, and nonsense individually presented words on a sample of 90 Grade Two and 89 Grade Three students in regular classrooms. They found that, while some students utilized both strategies, “one fifth attained average scores on irregular words but substantially below-average scores on nonsense words [sight word readers]… and one seventh showed the opposite pattern – average or better nonsense-word scores but poor irregular-word performance [decoders]” (p. 441). On comprehension tests, the sight word readers performed better than the decoders in Grade Two (Freebody et al., 1988). However, by Grade Three the “failure to acquire and use efficient decoding skills” decreased reading fluency and thus, comprehension scores (Freebody et al., 1988, p. 441). Therefore, over time the use of decoding strategies surpassed the use of sight word strategies. This may be explained by Gough’s (1993) finding that relying on sight word strategies is impeded by memorization and novel words. Gough explains that “while i’s easy to find a cue to distinguish one word from a few others, with each additional word it becomes harder” and sight word strategies do not help with “recognition of new words: knowing that ELEPHANT is the long word, or CAMEL is the one with humps, cannot help the child decode HORSE” (1993, p. 188). A benefit of decoding instruction is that readers have a way to access words and texts that they have not previously encountered (Eldredge et al., 1990; Ryder et al., 2007).

However, various benefits of sight word strategies are apparent in the literature. Eldredge et al. (1990) note that sight word reading allows for less “nonsense errors” but “advocates of explicit phonics approaches believe that making nonsense errors is a stage that passes” (p. 202). Sight word knowledge allows for fluent reading and thus, higher comprehension scores and vocabulary growth (Aaron et al., 1999; Eldredge et al., 1990; Ryder, 2007). This may be because “if readers attempt to decode words… their attention is shifted from the text to the word itself to identify it, and this disrupts comprehension, at least momentarily” (Ehri, 2005; Aaron et al., 1999). Sight word reading is unobtrusive and efficient (Ehri, 2004). On the other hand, Eldredge et al. (1990) note that “improved decoding skills provide the possibility for readers to give more attention to text message, resulting in better reading comprehension” (p. 202). If students have learned specific sight words, they often have proficient accuracy scores during reading benchmark assessments, making a sight word approach appealing to educators reporting reading scores.

The purpose of this study is to extend the research with a focus on beginning readers who are struggling. A 1997 study by Uhri and Shepherd looked at teaching decoding strategies as a prelude to sight word strategies for struggling readers and they found positive gains in both non-word and sight word reading scores (Uhry et al., 1997). It is important to replicate this study for learners who are experiencing difficulties “with the automatic mapping between print and speech” (Ehri, 2005, p. 172) so that our reading instruction can benefit all learners. While one strategy may not be superior to the other, Aaron (1999) notes that “efforts to improve sight-word reading skills of poor decoders through whole word methods by using flash cards or computers may not be very successful” (p. 119). In addition, “if readers do not know short vowel spellings, or they do not know that ph symbolizes /f/, then when they encounter these letters in particular words, the letters will not become bonded to their phonemes in memory” and this explicit instruction needs to occur for successful long-term reading (Ehri, 2005, p. 172; Eldredge et al., 1990; Weiser et al., 2011). It is important to determine if we are emphasizing sight word reading approaches to score higher on comprehension measures today, but overlooking the importance of decoding on reading comprehension scores over time.

Purpose Statement

The purpose of this quasi-experimental study (Creswell, 2012; Jackson et al., 2007; McMillan et al., 2010; Neuman, 2006) is to test the theory of learning to read that compares decoding to sight word instruction for Grade One students who are struggling to read (reading A to C as per Fountas and Pinnell (F&P) formative benchmarking). The independent variables are decoding and sight word reading strategies (defined above). The dependent variable of reading comprehension will be assessed through the Woodcock-Johnson Psycho-Educational Battery, Third Edition (WJ-III) Broad Reading Passage Comprehension subtest. Reading comprehension will operationally be defined as being able to orally relate “the sequence (i.e., beginning, middle, and end), the key points (who, what, when, where, and why) and the problems and solution” (Saskatchewan Curriculum, 2010, p. 27) both implicitly and explicitly stated of what one reads.

Hypothesis

Alternative Hypothesis: Grade One struggling readers in _______ school division who participate in decoding instruction will have greater reading comprehension scores than students who participate in sight word instruction.

Null Hypothesis: There is no difference between the treatment group (decoding instruction) and the control group (sight word instruction) in terms of reading comprehension for Grade One struggling readers in _______ school division.

Method

Subjects

The participants are three classrooms of Grade One students in an elementary school in ________ school division. Their ages range from six to seven years old and the students are of different sexes, races, and socio-economic classes. Thirty students (n=30) will be receiving reading intervention with a Student Support Teacher (n=1) due to being identified as struggling readers (reading A to C on F&P formative benchmarking). Students will take part in a one-on-one pretest where they read 20 irregular words, 20 regular words, and 20 nonsense words. Students who score less than 50% correctly will be randomly assigned to the control group, focusing on sight word instruction, or the treatment group, focusing on decoding instruction. Both groups will be taught by the same trained Student Support Teacher (n=1) during a different 30 minute period each day for twelve weeks (January to March). The timespan is short to avoid maturation and potential cross-over lessons from within the regular classroom setting. Students will take a posttest on irregular words, regular words, and nonsense words. Their reading comprehension will be benchmarked using the WJ-III.

Procedure

An application to the ethics board at the University of Regina will be made to grant approval to ethically conduct this research. The school division, the specific elementary school, and the participants’ caregivers will receive a formal letter explaining the purpose and benefit of the research, as well as specific details about the timespan, activities, and the use of data, paying specific attention to student anonymity (Creswell, 2012). All levels will have consent forms to sign and return in order for the research to be conducted.

Materials

Treatment Group – Decoding Control Group – Sight Words
Grapheme-Phoneme Relationships (5 minutes) – teaching phonics
generalizations, blends, digraphs, letter
sounds, consonant-vowel-consonant
(CVC) words, and vowel teams through
the use of the Letterland program stories, songs, and actions and the Grade One
curricular list of phonics generalizations
(ee, sh, ch, ing, etc.), blends and
diagraphs (bl, br, th, wh, etc.), vowel
teams (ea, oa, oo, etc.), and the
alphabet (Saskatchewan Ministry of
Education, 2010, p. 35)
Sight Word Naming (5 minutes)
teaching sight word recognition through
the Edmark program (Browder, 2012), a ‘Sight Word of the Day’ song, and word
learning through flashcard strategies and visual word boxes
Grapheme-Phoneme Manipulation (10 minutes) – using manipulatives (ex. magnetic letters, blocks, wooden letters, etc.) to segment and blend the sounds in words
and using Elkonin boxes to make word
changes
Sight Word Games (10 minutes) –
playing sight word games, such as
Concentration and Bingo, to practice the
sight words taught that day and
previously
Guided Reading (10 minutes) – applying grapheme-phoneme blending in context
to an appropriately leveled text
(approximately F&P levels A to C) (Uhry
et al., 1997; Weiser et al., 2011)
Guided Reading (10 minutes) – applying sight word knowledge in context to an
appropriately leveled text (approximately F&P levels A to C) (Uhry et al., 1997;
Weiser et al., 2011)
Writing (5 minutes) – writing about what was read to encourage comprehension
and practice segmenting and blending of phoneme-graphemes through invented
spelling (Uhry et al., 1997; Weiser et al.,
2011).
Writing (5 minutes) – writing about what was read to encourage comprehension
and practice sight words learned through word wall and textual cues (Uhry et al.,
1997; Weiser et al., 2011, p. 172).

Data Collection and Instruments

The students will take part in a one-on-one pretest where they read 20 irregular words, 20 regular words, and 20 nonsense words aloud (Eldredge et al., 1990; Freebody et al., 1988; Jeynes, 2008). A regular word will be defined as a word where each letter represents a common phoneme, whereas an irregular word may have silent letters, digraphs, blends, and/or vowel teams present (Freebody et al., 1988). A nonsense word will follow the grapheme-phoneme patterns of the language but result in a meaningless word, such as ‘bif.’ The same posttest will be used to determine their decoding and/or sight word strategy use after the intervention. The words will be taken from the appendix of regular, nonsense, and irregular words from Freebody’s and Byrne’s (1988) study (p. 453), keeping the grade difference in mind. The Word Attack and Letter-Word Identification subtests from the WJ-III will also be used but only during the posttest to reduce the threat of testing impact on internal validity.

Reading comprehension will be assessed using the Woodcock-Johnson Psycho-Educational Battery, Third Edition (WJ-III) by Woodcock, McGrew, and Mather (2001). The test was normed on 8,800 cases and its “internal consistency reliabilities range from .76 to .97 with a median of .87″ (Thorndike and Thorndike-Christ, 2010, p. 393). Cizek (2003) notes that the test “meets professional standards of reliability and validity for [its] intended purposes” (n.p.). The test is based on the Cattell-Horn-Carrol model of intelligence and achievement, which is commonly used in school psychology (Schrank, 2010). It is appropriate for ages 2 through 90 (Thorndike & Thorndike-Christ, 2010). The test “takes about 50 to 60 minutes to administer” if using all eleven subtests (Thorndike and Thorndike-Christ, 2010, p. 431). For the purpose of this study, the testing time will be reduced due to only using three subtests, which will help with maturation.

Data Analysis

The Equal Variance one-tailed t-test will be used to “determine the difference between the means of the two groups” to ensure significance is based on the intervention rather than a sampling error (Mertler et al., 2010, p. 90). A repeated measure t-test will also be used to compare the results of the pre- and posttests for the same individuals (Mertler et al., 2010). The groups are equal and there is one independent and one dependent variable. Once the data is produced, it will be analyzed through the Statistical Package for the Social Sciences (SPSS) program (Creswell, 2012) in a spreadsheet format.

The p-value will be set with a <.05 level of statistical significance (Neuman, 2011). Thus, if the results are less than this, we will “reject the null hypothesis and call the findings significant” (Mertler et al., 2010, p. 93). A p-value of <.05 is common in educational psychology research and is deemed appropriate for this study to avoid a type 1 or type 2 error (Neuman, 2011).

Limitations

Potential threats to internal and external validity are possible in all social research. Due the quasi-experimental nature of this study, the lack of random selection may cause an inequality between groups or selection bias from the onset (Creswell, 2012; Neuman, 2011). However, due to the ethical nature of research on students in premade classes, a true experiment with random sampling would not be applicable. Another internal threat may be testing effect since a pre- and posttest will be administered and students may remember items or simply improve their testing abilities (Creswell, 2012; Neuman, 2011). This can be solved with the Solomon-Four Group Design (Neuman, 2011). In this study, an additional posttest along with the original will be used. While we are using words from a previous research study and a standardized achievement test rather than the words taught in their classroom lessons, we cannot predetermine if students have been exposed to these words before and thus had a chance to learn them by sight. To ameliorate this, the criteria for inclusion is both struggling to read (reading F&P levels A to C) and 50% of the words stated incorrectly on the initial pretest. This should help eliminate ceiling scores. Students may also experience natural growth, testing boredom, or other natural causes that impact their results via maturation (Creswell, 2012; Neuman, 2011). A diffusion of treatment may occur if classroom instruction allows the treatment or control group to be exposed to the strategies of the other group (Neuman, 2011). The duration of the study is short so that classroom instruction will not interfere by teaching crossover items to students in the control and treatment groups and to avoid maturation. Furthermore, this study may lend itself better to a longitudinal study over a two to four year period so that the impacts of the instructional strategies can be observed overtime. A sample size of 30 was deemed acceptable as per Creswell’s (2012) recommendations for educational research. However, a larger sample size, or more importantly a more representative sample size (Neuman, 2011), may allow for more accurate generalizations.

Implications/Applications

The two overarching applications of this study for teachers will be clarity and training. Results of the study should assist teachers in planning for their classroom reading instruction (tier 1) and Student Support Teachers in planning specific reading interventions (tier 2) (Saskatchewan Provincial Reading Team, 2017). To the extent that the findings show that decoding should be emphasized for those beginning readers whom are struggling to read, teaching pedagogy may be shifted. Thus, the implication will be greater reading success for all students by “ameliorating early reading failure” (Weiser et al., 2011, p. 172) through a decoding approach. As Jeynes (2008) purported, “phonics instruction is a viable way of reducing the achievement gap” (p. 153); it is important to determine the best reading strategies through research and early intervention. This study should extend previous findings that all students “can learn decoding skills” (Browder, 2012, p. 243), albeit with explicit instruction and ample time. A change in pedagogy may also occur through teacher training in university education courses and/or professional development. The overall goal of the study is to provide concrete evidence towards a reading intervention strategy that will increase reading outcomes for all learners.

Works Cited

Aaron, P.G., Joshi, R.M., Ayotollah, M., Ellsberry, A., Henderson, J., Lindsey, K. (1999). Decoding and sight-word naming: Are they independent components of word recognition skill? Reading and Writing, 11(2), 89-127. doi: https://doi-org.libproxy.uregina.ca/10.1023/A:1008088618970

Browder, D., Ahlgrim-Delzell, L., Flowers, C., & Baker, J. (2012). An evaluation of a multicomponent early literacy program for students with severe developmental disabilities. Remedial and Special Education, 33(4), 237-246. doi:http://dx.doi.org/10.1177/0741932510387305

Chapman, M. L. (2003). Phonemic awareness: Clarifying what we know. Literacy Teaching and Learning, 7(1-2), 91-114. Retrieved from: https://login.libproxy.uregina.ca:8443/login?url=https://search.proquest.com/docview/1023533529?accountid=13480

Cizek, G. J. (2003). “Review of the Woodcock-Johnson III” in B. S. Plake, J. C. Impara, & R. A. Spies (Eds.), The fifteenth mental measurement yearbook (15th ed.), 1020-1024. Lincoln, NE: Buros Institute of Mental Measurements.

Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Boston, MA: Pearson Education.

Ehri, L. C. (2005) Learning to read words: Theory, findings, and issues. Scientific Studies of Reading, 9(2), 167-188. doi: 10.1207/s1532799xssr0902_4

Eldredge, J. L., Quinn, B., & Butterfield, D. D. (1990). Causal relationships between phonics, reading comprehension, and vocabulary achievement in the second grade. Journal of Educational Research, 83(4), 201-214. doi:https://doi-org.libproxy.uregina.ca/10.1080/00220671.1990.10885957

Fien, H., Smith, J. L. M., Smolkowski, K., Baker, S. K., Nelson, N. J., & Chaparro, E. (2015). An examination of the efficacy of a multitiered intervention on early reading outcomes for first grade students at risk for reading difficulties. Journal of Learning Disabilities, 48(6), 602-621. doi:http://dx.doi.org/10.1177/0022219414521664

Freebody, P., & Byrne, B. (1988). Word-reading strategies in elementary school children: Relations to comprehension, reading time, and phonemic awareness. Reading Research Quarterly, 23(4), 441-453. doi:10.2307/747642

Gough, P.B. (1993). The beginning of decoding. Kluwer Academic Publishers, 5(2), 181-192. doi: https://doi-org.libproxy.uregina.ca/10.1007/BF01027483

Herbert, Michael. (2005). “WJ-III Information Packet” [PDF Document]. Retrieved from: https://brookeblonquist.weebly.com/uploads/2/3/0/7/23078850/wjiii_information_packet__from_updc__1.pdf

Jackson, W., & Verberg, N. (2007). “Approaches to methods” in Methods: Doing social research (4th ed.), 3-22. Toronto, ON: Pearson Prentice-Hall Canada.

Jeynes, W. H. (2008). A meta-analysis of the relationship between phonics instruction and minority elementary school student academic achievement. Education and Urban Society, 40(2), 151-166. doi:10.1177/0013124507304128

McMillan, J. H., & Schumacher, S. (2010). “Research designs and reading research articles” in Research in education: Evidence-based inquiry (7th ed.), 19-45. Toronto, ON: Pearson.

Mertler, C. A., & Charles, C. M. (2011). “Interpreting and summarizing published research” in Introduction to educational research (7th ed.),79-97. Toronto, ON: Pearson.

National Reading Panel (U.S.) (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction [Reports of the subgroups]. National Institute of Child Health and Human Development (U.S). Retrieved from: https://www.nichd.nih.gov/sites/default/files/publications/pubs/nrp/Documents/report.pdf

Neuman, W. L. (2011). Social research methods: Qualitative and quantitative approaches (7th). Toronto, ON: Allyn and Bacon.

Office of Special Education Frederick County Public Schools (2014). “Woodcock-Johnson IV Test of Achievement Administration Training Manual” [PDF Document]. Retrieved from: https://education.fcps.org/specialeducation/sites/specialeducation/files/the_ woodcock_johnson_iv_training_manual.pdf

Ryder, J. F., Tunmer, W. E., & Greaney, K. T. (2008). Explicit instruction in phonemic awareness and phonemically based decoding skills as an intervention strategy for struggling readers in whole language classrooms. Reading and Writing: An Interdisciplinary Journal, 21(4), 349-369. doi: http://dx.doi.org/10.1007/s11145-007-9080-z

Saskatchewan Ministry of Education. (2010). The Saskatchewan curriculum grades 1-3: English language arts. Retrieved from:https://www.curriculum.gov.sk.ca/webapps/moe-curriculum-BBLEARN/Home?language=en

Saskatchewan Provincial Reading Team. (2017). Saskatchewan reads: A companion document to the Saskatchewan English language arts curriculum – grades 1, 2, 3. Retrieved from: https://saskatchewanreads.wordpress.com/

Schrank, Frederick A. (2010). “Woodcock-Johnson III Tests of Cognitive Abilities” [PDF Document] in Handbook of Pediatric Neuropsychology (1st ed.), 1-20. Retrieved from: http://www.iapsych.com/articles/schrank2010ip.pdf

Thorndike, R. M., & Thorndike-Christ, T. (2010). Measurement and evaluation in psychology and education (8th ed.). Upper Saddle River, NJ: Pearson/Merrill Prentice Hall.

Uhry, J., & Shepherd, M. (1997). Teaching phonological recoding to young children with phonological processing deficits: The effect on sight-vocabulary acquisition. Learning Disability Quarterly, 20(2), 104-125. doi:10.2307/1511218

Weiser, B., & Mathes, P. (2011). Using encoding instruction to improve the reading and spelling performances of elementary students at risk for literacy difficulties: A best-evidence synthesis. Review of Educational Research, 81(2), 170-200. doi:http://dx.doi.org/10.3102/0034654310396719

Research Paper: Overlooking Childhood Trauma when Diagnosing Attention-Deficit Hyperactivity Disorder (ADHD)

Abstract

This paper explores the connection between trauma and ADHD, in terms of symptomology and etiology. Current diagnostic assessment methods for ADHD are inadequate for those who have experienced trauma. A call for more integrative, trauma-focused screening methods when diagnosing and treating ADHD is recommended.

Keywords: Acute Stress Disorder, adverse childhood experiences (ACEs), Attention-Deficit Hyperactivity Disorder (ADHD), childhood trauma, comorbidity, complex trauma, Disinhibited Social Engagement Disorder (DSED), evidence-based treatments, interpersonal trauma, Posttraumatic Stress Disorder (PTSD), Reactive Attachment Disorder (RAD), trauma screening

Introduction

Attention-Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that manifests in early childhood and presents as predominantly inattentive (ADHD-PI), predominantly hyperactive-impulsive (ADHD-HI), or combined type (ADHD-C). The severity ranges from mild to severe based on the number of symptoms present across two or more settings, as well as the impairment these symptoms have on the individual’s overall functioning (American Psychiatric Association [APA], 2013). Mash and Wolfe (2019) note that the prevalence of an ADHD diagnosis is “about 5% to 9% of all children and adolescents 4 to 17 years old in North America” (p. 244). The DSM-5 reports rates of 5% in children due to lower worldwide occurrences (APA, 2013). However, despite varying prevalence rates, ADHD is reported in every country that studies it, across all socioeconomic statuses (SES), and amongst males and females at a 2-3:1 ratio respectively (Mash & Wolfe, 2019). ADHD is considered to be a pervasive, lifelong disorder with varying patterns of behavior and intensity based on developmental levels (Mash & Wolfe, 2019). Since ADHD is a common referral problem, it is imperative that the diagnostic screening and assessment tools used are both valid and reliable.

When diagnosing ADHD, it is important to ascertain whether the symptoms are developmentally appropriate or a result of another medical, mental, or neurodevelopmental disorder (APA, 2013). This poses a challenge because approximately “80% of clinic-referred children with ADHD have a co-occurring psychological disorder” (Mash & Wolfe, 2019, p. 244; Canadian ADHD Resource Alliance [CADDRA], 2018), with the DSM-5 highlighting Antisocial Personality Disorder (ASPD), Autism Spectrum Disorder (ASD), Conduct Disorder (CD), Disruptive Mood Dysregulation Disorder (DMDD), Intermittent Explosive Disorder (IED), Major Depressive Disorder (MDD), Obsessive-Compulsive Disorder (OCD), Oppositional Defiance Disorder (ODD), Specific Learning Disorder (SLD), and anxiety, personality, psychotic, substance use, and tic disorders as potential comorbid or differential diagnoses (APA, 2013). In addition, Bipolar Disorder (BP), Intellectual Developmental Disorder (IDD), Reactive Attachment Disorder (RAD), and neurocognitive disorders are included as differential diagnoses to be considered (APA, 2013). Accounting for potential comorbid and differential diagnoses, ensures an accurate diagnosis and treatment plan. While the DSM-5 includes many comorbid and differential diagnoses for consideration, a growing body of research highlights the need for trauma screening when diagnosing ADHD due to the relational course and symptomology.

Traumatic events may be termed in the literature as complex trauma (Conway, Oster, & Szymanski, 2011; Pottinger, 2015), interpersonal trauma (Mash & Wolfe, 2019), and/or adverse childhood experiences (ACEs) (Conway et al., 2011; Brown et al., 2017). Like ADHD, trauma does not discriminate: “in 2017, there were 59,236 child and youth victims (aged 17 years and younger) of police-reported violence in Canada… overall, 33% of children and youth victims had been subjected to violence by a casual acquaintance and 18% by a stranger” (Burczycka, Conroy, & Savage, 2018, p. 4). This is a reduction from the 85,440 substantiated cases in 2008 (Klien, Daminai-Taraba, Koster, & Campbell, 2015). These types of violence included complex and interpersonal forms of trauma, such as neglect, sexual assault, and physical and emotional abuse. These experiences in childhood can lead to diagnosable trauma- and stressor-related disorders such as Acute Stress Disorder, Disinhibited Social Engagement Disorder (DSED), Posttraumatic Stress Disorder (PTSD), and Reactive Attachment Disorder (RAD) in 10-20% of cases (APA, 2013). However, whether diagnosable or not, trauma has a negative impact on childhood development. Based on the 1998 ACEs study, 11-23% of adults have experienced childhood trauma that can “impede an individual’s ability to integrate sensory, emotional, and cognitive information” and present as hyperarousal (Conway et al., 2011, p. 61-2). Having ACE scores increases “a child’s risk for toxic levels of stress, which in turn might impair neurodevelopment, behavior, and overall physical and mental health” (Brown et al., 2017, p. 349-50). Unfortunately, while childhood trauma is far-reaching, this is not often the case for trauma screening.

The ADHD and Trauma Connection

Within the research, the connection between trauma and ADHD has been established. For instance, Ford et al. (2000) found a strong correlation between ADHD and trauma; 25% and 11% of individuals with ADHD experienced physical and sexual abuse respectively and rates of trauma rose to 91% with comorbid ODD. Weinstein, Staffelbach, and Biaggio (2000) also found a correlation between sexual abuse and ADHD. In 2006, Endo, Sugiyama, and Someya found that 14-46% of children with ADHD had experienced abuse. Similarly, Briscoe-Smith and Hinshaw (2006) found that 6 to 12 year old girls with ADHD had experienced higher rates of abuse than the general public – 14.3% to 4.5% respectively. They found that the girls with ADHD who experienced abuse often presented with externalizing symptoms and combined type ADHD. Rucklidge, Brown, Crawford, and Kaplan (2006) surveyed adults with ADHD using the Childhood Trauma Questionnaire and 56% of the individuals with ADHD self-reported childhood trauma. Conway et al. (2011) studied 79 children ages 8 to 18 from Hispanic and African-American backgrounds in an urban psychiatric hospital and found that those with ADHD experienced trauma at higher rates than the general public. Perry and Mackinnon (2012) purported that developmental adversity is a risk factor for the expression of ADHD. In 2013, Biederman et al. studied children in a pediatric setting and found that children from families with higher levels of interpersonal conflict had disproportionately higher rates of ADHD.

While these comparisons were based off of DSM-IV-R assessment criteria, recent studies using DSM-5 diagnostic criteria continue to connect ADHD to trauma. Klein et al. (2015) studied Canadian children in child protection services and found that they “are diagnosed and treated for… ADHD at higher rates than the general population” due to symptom overlap (p. 178). Fuller-Thomson and Lewis (2015) had Canadian adults self-report past childhood physical abuse, sexual abuse, and domestic violence. They found that the first two adverse experiences elevated odds of an ADHD diagnosis in both women and men, whereas domestic violence elevated odds of an ADHD diagnosis in women only. Brown et al. (2017) used a sample of 76,277 children ages 4 to 17 and found that ACE scores and ADHD were associated. Furthermore, they found a gradual relationship between the number of ACE scores and the severity of the ADHD presentation (Brown et al., 2017). In their brain neuroimaging research, Park et al. (2017) found that childhood trauma “strongly predicts the development of ADHD and influences biological processes in offspring” (p. 184). Thus, a clear relationship among trauma and ADHD continues to be substantiated in the literature, yet relatively overlooked in current DSM-5 diagnostic criteria and assessment practices.

Shared Etiology and Symptomology in ADHD and Trauma

ADHD and trauma share similar etiologies and symptomologies. While neurobiological factors rather than psychological factors are often the focus for ADHD and vice versa for trauma, a more integrative approach is preferred. Looking at neurobiological factors, Mash and Wolfe (2019) note that “ADHD appears to be related to abnormalities and developmental delays in the frontostriatal circuitry of the brain and pathways connecting this region with the limbic system, the cerebellum, the thalamus, and the default mode network” (p. 256). Trauma impacts areas of the brain connected to stress, such as the limbic and neuroendocrine systems (Mash & Wolfe, 2019). Similar deficits can be observed in the prefrontal cortex and in gray and white matter abnormalities. Spitzer, Schrager, Imagawa, and Vanderbilt (2017) studied children with PTSD and found that they had “reduced N-acetyl aspartate (NAA), indicating loss of neuronal integrity, in the medial prefrontal cortex… implying a common neuroanatomical etiology” with ADHD brain patterns (p. 345). Similarly, Perry and Mackinnon (2012) found that neglect can lead to an underdeveloped prefrontal cortex and reduced gray matter, leading to externalizing behaviors of impulsivity and reactivity or internalizing behaviors of withdrawal. Park et al. (2016) found white matter anomalies in children with ADHD and in those who had experienced childhood trauma. Furthermore, Park et al. (2017) researched catechol-o-methyltransferase genes on inhibitory deficits in children with ADHD and found “a genetic influence on the association between childhood trauma and the severity of inhibitory deficits in children with ADHD” (p. 183). While an in-depth exploration of brain functioning is beyond the scope and sequence of this research paper, it is important to note the brain connections between childhood trauma and ADHD that may result in similar behavioral presentations.

Psychological factors that are shared amongst ADHD and trauma include low SES, parental separation and divorce, parental mental illness, maternal substance use during pregnancy, and birth complications (Brown et al., 2017; Conway et al., 2011; Dubowitz et al., 2011; Gul & Gurkan, 2018; Mash & Wolfe, 2019; Richards, 2013). Mash and Wolfe (2019) recognize that “family problems may lead to greater severity of symptoms and to the emergence of co-occurring conduct problems” (p. 256), even though ADHD is generally not thought of as being caused by psychosocial factors. Furthermore, stigmatization and lack of family supports and resources can lead to mismanagement and misdiagnosis of symptoms (Fuller-Thomson & Lewis, 2015; Pottinger, 2015; Richards, 2012).

Symptoms of trauma, especially those related to PTSD, often mimic ADHD-like symptoms of hyperactivity and inattention. For instance, internalizing and externalizing behaviors such as inattention, distractibility, disruption, fidgeting, hyperactivity, restlessness, impulsivity, irritability, and poor emotional regulation may be observed in both cases (Briscoe-Smith & Hinshaw, 2006; Conway et al., 2011; Dahmen, Purtz, & Herpertz-Dahlmann, 2012; Endo et al., 2006; Ford et al., 2000; Klein et al., 2014; Park et al., 2017; Perry, 2007; Rucklidge et al., 2006; Spitzer et al., 2017; Szymanski, Sapanski, & Conway, 2011; Weinstein et al., 2000). Spitzer et al. (2017) found that when children cannot rely on a caregiver they adapt in ways that seem disruptive and “may present with signs and symptoms similar to ADHD” (p. 345). ADHD is listed as a differential or comorbid disorder in DSED due to similar impulsivity symptoms (APA, 2013). However, DSED is not listed as a differential or comorbid diagnosis for ADHD despite symptom overlap.

It has been argued that the externalizing symptoms of ADHD are easier to identify than the re-experiencing or avoidance symptoms related to PTSD and trauma, especially in young children (Ford et al., 2000; Klein et al., 2014; Spitzer et al., 2017; Szymanski et al., 2011; Young, Kenardy, & Cobham, 2011). The symptoms can impact relationships, academic performance, and executive functioning (Mash & Wolfe, 2019; Pottinger, 2015). In their study of Canadian children in the welfare system, Klein et al. (2015) found that the anxiety and hypervigilance response to trauma can mimic the hyperactivity and impulsivity found in ADHD. Furthermore, trauma-related avoidant behaviors can present like inattention in ADHD (Spitzer et al., 2017; Szymanski et al., 2011; Weinstein et al., 2000). When both disorders are present, trauma can exasperate symptoms since issues with coping and listening can further create a dysregulated affect (Szymanski et al., 2011). Because the symptoms of trauma and ADHD are closely related, a clinician may miss the signs of trauma and attribute behaviors solely to ADHD.

Evidence-Based Treatment

While the two disorders share behavioral symptoms, the treatment methods and approaches differ. The cost of ADHD in the United States varies between 12 to 17 thousand USD per person due to medical and educational needs (Klein et al., 2015; Mash & Wolfe, 2019). Thus, it is important that the treatments used are evidence-based and tailored to an accurate diagnosis so that they are both helpful and cost-effective. Treatment of ADHD often involves parent management training (PMT), educational and environmental interventions, and/or stimulant medications, such as dextroamphetamine, amphetamine-dextroamphetamine, and methylphenidate (CADDRA, 2018; Conway et al., 2011; Mash & Wolfe, 2019; Richards, 2013). Pharmacotherapy treatment is a common approach backed by the Multimodal Treatment of Attention Deficit Hyperactivity Disorder (MTA) study,but in complicated situations medications should be used in combination with psychoeducational interventions (Klein et al., 2014; Mash & Wolfe, 2019). ADHD treatments focus on treating the behavioral symptoms, whether through stimulant medications and/or environmental adaptations.

Treating trauma, on the other hand, focuses on the root cause(s) first and the specific behavioral symptoms second. These evidence-based treatments include Trauma-Focused Cognitive Behavioral Therapy (TF-CBT), psychotherapy, parent management training through the Triple P Program and Project Safe Care, and/or serotonergic antidepressants for PTSD specifically (Conway et al., 2011; Mash & Wolfe, 2019; Spitzer et al., 2017). The most common approach for PTSD treatment is TF-CBT, which incorporates elements of exposure therapy, narrative writing, role-play perspective taking, parental involvement, family communication, parental training, psychoeducation, safety, and relaxation, self-regulation, and stress management skills (Mash & Wolfe, 2019; Pottinger, 2015; Weisz & Kazdin, 2017). For those diagnosed with RAD or DSED, parenting classes, environmental changes, and counselling are the preferred methods over psychopharmacological treatments (Mash & Wolfe, 2019; Perry & Mackinnon, 2012). In addition, building on protective factors such as family and social supports (Perry & Mackinnon, 2012), connecting families to support resources (Dubowitz et al., 2011), and Duty to Report protocol in childcare professions can support trauma treatment.

At best mistreatment could lead to ineffective approaches; at worst mistreatment could lead to potential harm. For instance, Klein et al. (2015) note concerns such as “prolonged exposure to unhelpful medications, stigmatization, a feeling of being misunderstood and opportunity cost in treating other problems” (p. 183). Furthermore, mistreatment neglects “the underlying emotional, personality, and interpersonal issues” that the child may have (Conway et al., 2011, p. 6). Richards purports that treating children who have experienced trauma with stimulant medication “runs the risk of colluding with an external environment which needs to change, and effectively ‘silencing’ the mechanisms a child is using to communicate that ‘all is not well'” (2013, p. 496). Because ADHD treatments focus on the behaviors, using these treatments with those who have experienced trauma does little to help the child and may overlook the relational and familial problems (Richards, 2013). Briscoe-Smith et al. (2006) found the following:

There are children with ADHD for whom abuse appears to be overlooked diagnostically, either as an etiological factor or an exacerbating variable. If such trauma is not addressed, symptoms associated with it may go unchecked and may even become worse as the child develops. The usual interventions for ADHD (behavioral modification procedures, stimulant medications) may not be the appropriate treatments for traumatized children. (p. 10)

Furthermore, if ADHD-based treatments are used without trauma supports, “symptoms and functional impairments may persist” (Klein et al., 2015, p. 181). Misdiagnosis and thus, mistreatment is predictive of negative outcomes.

If a child has ADHD but also a history of trauma, it is important not to treat each in a vacuum. Not only would the developmental course be more severe (Biederman et al., 2012; Brown et al., 2017; Ford et al., 2000; Szymanski et al., 2011), but both the trauma and ADHD symptoms would require monitoring. Brown et al. (2017) note that “cumulative exposure to traumatic experiences is associated with worse overall ADHD symptom severity” and may explain why solely using ADHD treatments does not work (p. 353). Ensuring safety and trauma symptom stabilization is recommended before treating the comorbid ADHD (Biederman et al., 2013; Perry & Mackinnon, 2012). While children who experience trauma may require medications and behavioral management strategies as part of their treatment, especially when comorbid ADHD occurs, a typical approach would be therapeutic or caused-based, followed by medications or behavior-based treatments. Further research on specific, research-based trauma and ADHD treatments is needed (Briscoe-Smith et al., 2006). Pottinger (2015) has adapted trauma-based strategies to support clients with comorbid ADHD but continued work in the field would be beneficial to ensure validity and reliability.

Moving Forward with Trauma Screening

ADHD and childhood trauma are closely related; thus, it is integral to have screening tools and methods that differentiate between the two. Unfortunately, despite research, trauma screening is not mandatory when exploring an ADHD diagnosis. Spitzer et al. (2017) found that only 44% of general practitioners screened for trauma. Furthermore, Brown et al. (2017) note that “although it has been shown that children exposed to ACEs can manifest many of the disruptive behaviors, impulsivity, and executive dysfunction characteristics of ADHD, comprehensive evaluation for traumatic stressors is not routinely performed during ADHD assessment” (p. 350). They found that only 2-4% of general practitioners routinely screened for ACEs and for one third, trauma screening was not part of their practice. The Canadian ADHD Practice Guidelines briefly mention exploring trauma histories but no specific screening tools are recommended (CADDRA, 2018). The DSM-5 recommends excluding other mental disorders and Reactive Attachment Disorder (RAD) is included as a differential diagnosis with differences in the amount of symptoms shown and attachment styles (APA, 2013). However, research by Szymanski et al. (2011) and Conway et al. (2011) shows that there is diagnostic ambiguity and confusion with determining differential diagnoses. This may be because each child differs in their behavioral presentation. Moving forward, trauma screening should become commonplace to ensure accurate diagnosis, proper care, and cost-effectiveness of treatments.

If trauma screening is to become best practice, having the appropriate tools is necessary. Currently, a pediatrician or family physician would work with an educational psychologist to diagnose ADHD (CADDRA, 2018). Often it is the caregiver or educator whom makes the initial referral and acts as a main source of screening information (Klein et al., 2015), because they have firsthand experience with the child. Since there are no definitive diagnostic tools for ADHD, clinical judgement and triangulation of assessments from multiple sources is necessary. These assessments may include parent and teacher rating scales, such as the Conners Comprehensive Behavior Rating Scales-3 (Conners CBRS-3), Vanderbilt ADHD Diagnostic Rating Scales (VADRS), ADHD Rating Scale, SNAP-IV Teacher and Parent Rating Scales, and Child Behavior Checklist (CBCL) (CADDRA, 2018; Gupta & Kar, 2010). It is important to note that none of these rating scales are intended to diagnose or screen for trauma (Spitzer et al., 2017; Weinstein et al., 2000) and rater-bias may occur (Gupta & Kar, 2010). Furthermore, Brown et al. (2017) report that:

Current rating scales and checklists focus primarily on presenting behaviors and do not query about psychosocial and environmental factors, such as exposure to traumatic stress, which might play an important role in ADHD symptom onset and progression and if identified, can help clinicians determine helpful components of multimodal therapy. (p. 350)

From a best-practice standpoint, the connection between trauma and ADHD should lend itself to clinical consideration of both concerns even when a diagnosis of ADHD seems obvious.

Moving forward, clearer diagnostic guidelines, mandatory trauma screening protocol, and more education on the relationship between trauma and ADHD would be beneficial. Furthermore, including trauma as a comorbid or differential diagnosis to ADHD would help foster accurate diagnoses. Multi-agency collaboration between child protection workers, educators, psychologists, pharmacists, and doctors may help support accurate diagnosis of comorbid or differential ADHD and trauma. Asking direct questions about experiences of abuse and other trauma, probing further with similar symptomology, exploring developmental histories, observing children in their natural environments, and using rating scales in addition to written self-reports and medical exams is recommended (Mash & Wolfe, 2019; Ford et al., 2000; Richards, 2013; Weinstein et al., 2000). In addition, asking targeted questions about onset, duration, frequency, thoughts and feelings, environments, activities, family relationships, and the people around when certain symptoms occur is warranted to determine patterns of ADHD-like behavior from trauma-related symptoms. All children deserve an accurate diagnosis and treatment plan that deals with the complexity of their lives; we need an integrative, all-encompassing approach to diagnosing ADHD so that trauma will not be overlooked for any child with the misfortune.

Works Cited

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

Biederman, J., Petty, C. R., Spencer, T. J., Woodworth, K. Y., Bhide, P., Zhu, J., & Faraone, S. V. (2013). Examining the nature of the comorbidity between Pediatric Attention Deficit/Hyperactivity Disorder and Post-Traumatic Stress Disorder. Acta Psychiatrica Scandinavica, 128(1), 78-87. doi:10.1111/acps.12011.

Briscoe-Smith, Allison M., & Hinshaw, S. P. (2006). Linkages between child abuse and Attention-Deficit/Hyperactivity Disorder in girls: Behavioral and social correlates. Child Abuse & Neglect, 30(11), 1239-1255. doi:10.1016/j.chiabu.2006.04.008.

Brown, N. M., Brown, S. N., Briggs, R. D., German, M., Belamarich, P. F., & Oyeku, S. O. (2017). Associations between adverse childhood experiences and ADHD diagnosis and severity. Academic Pediatrics, 17(4), 349-355. doi:10.1016/j.acap.2016.08.013.

Burczycka, M., Conroy, S., & Savage, L. (2018). Family violence in Canada: A statistical profile, 2017. Juristat: Canadian Center for Justice Statistics, 37(1), 1-56.

Canadian ADHD Resource Alliance (CADDRA). Canadian ADHD Practice Guidelines, Fourth Edition, Toronto ON: CADDRA, 2018.

Conway, F., Oster, M., & Szymanski, K. (2011). ADHD and complex trauma: A descriptive study of hospitalized children in an urban psychiatric hospital. Journal of Infant, Child, and Adolescent Psychotherapy, 10(1), 60-72. doi:10.1080/15289168.2011.575707.

Dahmen, B., Putz, V., Herpertz-Dahlmann, B., & Konrad, K. (2012). Early pathogenic care and the development of ADHD-like symptoms. Journal of Neural Transmission, 119(9), 1023-1036. doi:10.1007/s00702-012-0809-8.

Dubowitz, H., Kim, J., Black, M. M., Weisbart, C., Semiatin, J., & Magder, L. S. (2011). Identifying children at high risk for a child maltreatment report. Child Abuse & Neglect, 35(2), 96-104. doi:10.1016/j.chiabu.2010.09.003.

Endo, T., Sugiyama, T., & Someya, T. (2006). Attention-Deficit/Hyperactivity Disorder and Dissociative Disorder among abused children. Psychiatry and Clinical Neurosciences, 60(4), 434-438. doi:10.1111/j.1440-1819.2006.01528.

Ford, J. D., Racusin, R., Ellis, C. G., Daviss, W. B., Reiser, J., Fleischer, A., & Thomas, J. (2000). Child maltreatment, other trauma exposure, and posttraumatic symptomatology among children with Oppositional Defiant and Attention Deficit Hyperactivity Disorders. Child Maltreatment, 5(3), 205-217. doi:10.1177/1077559500005003001.

Fuller-Thomson, E., & Lewis, D. A. (2015). The relationship between early adversities and Attention-Deficit/Hyperactivity Disorder. Child Abuse and Neglect, 47, 94-101. doi:10.1016/j.chiabu.2015.03.005.

Gul, H., & Gurkan, C. K. (2018). Child maltreatment and associated parental factors among children with ADHD: A comparative study. Journal of Attention Disorders, 22(13), 1278-1288. doi:10.1177/1087054716658123.

Gupta, R., & Kar, B. (2010). Specific cognitive deficits in ADHD: A diagnostic concern in differential diagnosis. Journal of Child and Family Studies, 19(6), 778-786. doi: 10.1007/s10826-010-9369-4

Klein, B., Damiani-Taraba, G., Koster, A., Campbell, J., & Scholz, C. (2015). Diagnosing Attention-Deficit Hyperactivity Disorder (ADHD) in children involved with child protection services: Are current diagnostic guidelines acceptable for vulnerable populations? Child: Care, Health and Development, 41, 178-185. Doi: 10.1111/cch.12168

Mash, E.J. & Wolfe, D. A. (2019). Abnormal Child Psychology (7th Ed.). Belmont, CA: Wadsworth, Cengage Learning.

Park, S., Kim, B. N., Kim, J. W., Shin, M. S., Yoo, H. J., & Cho, S. C. (2017). Interactions between early trauma and catechol-o-methyltransferase genes on inhibitory deficits in children with ADHD. Journal Of Attention Disorders, 21(3), 183-189. doi:10.1177/1087054714543650.

Park, S., Lee, J. M., Kim, J. W., Kwon, H., Cho, S. C., Han, D. H., Cheong, J. H., & Kim, B. N. (2016). Increased white matter connectivity in traumatized children with Attention Deficit Hyperactivity Disorder. Psychiatry Research-Neuroimaging, 247, 57-63. doi:10.1016/j.pscychresns.2015.09.012.

Perry, B. D., & Mackinnon, L. (2012). The neurosequential model of therapeutics: An interview with Bruce Perry. Australian and New Zealand Journal of Family Therapy, 33(3), 210-218.

Perry, B. D. (2007). Stress, trauma, and post-traumatic stress disorders in children: An introduction [PDF File]. The Child Trauma Academy. Retrieved from: https://childtrauma.org/wp-content/uploads/2013/11/PTSD_Caregivers.pdf

Pottinger, A. (2015). The use of trauma counseling for children with Attention-Deficit Hyperactivity Disorder. International Journal for the Advancement of Counselling, 37(1), 17-27. doi:10.1007/s10447-014-9222-3.

Richards, L. M. (2013). It is time for a more integrated bio-psycho-social approach to ADHD. Clinical Child Psychology and Psychiatry, 18(4), 483-503. doi:10.1177/1359104512458228.

Rucklidge, J. J., Brown, D. L., Crawford, S., & Kaplan, B. J. (2006). Retrospective reports of childhood trauma in adults with ADHD. Journal of Attention Disorders, 9(4), 631-641. doi:10.1177/1087054705283892.

Spitzer, J., Schrager, S. M., Imagawa, K. K., & Vanderbilt, D. L. (2017). Clinician disparities in anxiety and trauma screening among children with ADHD: A pilot study. Children’s Health Care, 46(4), 344-355. doi:10.1080/02739615.2016.1193809.

Szymanski, K., Sapanski, L., & Conway, F. (2011). Trauma and ADHD – association or diagnostic confusion? A clinical perspective.” Journal of Infant, Child, and Adolescent Psychotherapy, 10(1), p. 51-59. doi:10.1080/15289168.2011.575704.

Weinstein, D., Staffelbach, D., & Biaggio, M. (2000). Attention-Deficit Hyperactivity Disorder and Posttraumatic Stress Disorder: Differential diagnosis in childhood sexual abuse. Clinical Psychology Review, 20(3), 359-378. doi: 10.1016/S0272-7358(98)00107

Weisz, J. & Kazdin, A. (2017). Evidence-based Psychotherapies for Children and Adolescents (3rd ed.) New York, NY: The Guilford Press.

Young, A., Kenardy, J., & Cobham, V. (2011). Trauma in early childhood: A neglected population. Clinical Child and Family Psychology Review, 14(3), 231-250. doi: 10.1007/s10567-011-0094-3