Socio-Cultural Psychology in Practice

Socio-Cultural Psychology in Practice


It is common for educational psychologists to recommend best-practice interventions and teaching methods, often after completing a psychoeducational assessment or in response to a referral question. However, their involvement should not stop there; assisting teachers to employ best-practice teaching strategies and methods can be rewarding for all involved. Challenges can arise, however, if the educational psychologist’s and teacher’s perspectives do not align. In these instances, how the discrepancy is handled can make all the difference in interventions being employed with fidelity. The implementation model by Jolliffe (2015) will be used throughout this discussion to demonstrate how to bridge two differing perspectives. Jolliffe’s (2015) model begins with a theoretical basis and shifting of existing beliefs. It then progresses to experiencing the new method directly and concludes with increasing competency and sustaining learning (Jolliffe, 2015). The case scenario, used to demonstrate this progression, involves a teacher that is adamant towards the use of direct instruction despite recognition that this approach is not working for all learners, particularly those individuals with developmental disabilities. On the other hand, the educational psychologist recommends cooperative learning, as “higher effect sizes tend to be associated with approaches which combine group goals and individual accountability” (Topping, 2005, p. 632). Finding a compromise between these two diverse teaching methods will ultimately lead to greater gains for all involved.

Theoretical Basis: Direct Instruction

Direct instruction is defined as “a collection of instructional practices combined together to design and deliver well-crafted lessons that explicitly teach grade level content to all students” (Hollingsworth & Ybarra, 2009, p. 12). Direct instruction is a research-based method that involves demonstrating, explaining, modeling, scaffolding, group work, and immediate feedback (Archer et al., 2011). Lessons typically start with objectives and connections to prior knowledge (Archer et al., 2011). Direct instruction is a teacher-directed approach, with the teacher explaining the concepts and their importance (Archer et al., 2011). Students practice new skills in whole and small groups with teacher guidance and the lessons typically conclude with individual practice and a closure activity (Archer et al., 2011). One method that encapsulates this process is the Gradual Release of Responsibility (GRR). Through the GRR, concepts progress from teacher, to whole group, to small group, and to individual practice. This can be described as ‘I Do, We Do, You Do it Together, You Do it Alone.’ Opportunities for students to respond and practice the skills increase with each stage. Direct instruction is content- and curricular-focused and originates from behaviour analytic psychology.

Theoretical Basis: Cooperative Learning

Cooperative learning, on the other hand, comes from socio-cultural psychology. The cooperative learning method stems from Vygotsky’s work on the Zones of Proximal Development and Piaget’s theory that learning must occur through interaction (Malmgren, 1998). Vygotsky believed that students could reach their full potential by working with slightly more advanced peers (Malmgren, 1998). This method is jointly beneficial (Topping, 2005); while the higher achieving peer is modeling the behaviour and skill for the other child, they solidify their own knowledge through teaching the concepts. Johnson and Johnson (1999) define cooperative learning as “the instructional use of small groups in which students work together to maximize their own and each other’s learning” (p. 73). This approach is suitable for any subject and grade. There are five main elements: “positive interdependence, individual accountability, promotive interaction, appropriate use of social skills, and periodic [group] processing of how to improve the effectiveness of the group” (Johnson & Johnson, 1999, p. 73). All five of these elements must be intentionally planned and included, making cooperative learning different than peer tutoring and typical group work (Jolliffe, 2015).

Theoretical Basis: Elements of Cooperative Learning

Each element of cooperative learning works together to produce benefits for all learners. Positive interdependence – which is often overlooked in traditional small group approaches – occurs when students believe that their efforts and outcomes are intertwined with the group (Johnson & Johnson, 2009; Jolliffe, 2015; Kuntz et al., 2001; Malmgren, 1998). This leads to increased responsibility because individual efforts impact the group, in addition to the individual (Johnson & Johnson, 2009). Furthermore, because the “individual’s success depends on the success of the group, students want their peers to do well” (Kuntz et al., 2001, p. 43). While positive interdependence leads to group accountability, there are also individual accountability measures. Johnson and Johnson (1999) note that “individual performance is checked regularly to ensure that all students are contributing and learning. The result is that the group is more than a sum of its parts, and all students perform higher academically than they would if they worked alone” (p. 68). It is important to connect individual responsibility back to the group, such as sharing individual growth (Johnson & Johnson, 1999).

Promotive interaction occurs as students work on a common task and goal (Johnson & Johnson, 1999). Through group problem-solving and discussions, students have increased opportunities to respond and this leads to improved social and academic results (Johnson & Johnson, 1999; Malmgren, 1998; Siegel, 2005). Promotive interaction differs from other approaches, as it involves specific roles being assigned (Bryant & Bryant, 1998; Hannon & Ratliffe, 2004; Johnson & Johnson, 2009; Kuntz et al., 2001; Prater et al., 1998). Students must share resources, distribute the workload, and cooperate for the common good of the group, creating a positive classroom climate and increased participation (Hannon & Ratliffe, 2004; Jenkins et al., 2003; Kuntz et al., 2001). Through this process, transferable social skills are developed (Topping, 2005). Social skills must be explicitly taught around “leadership, decision-making, trust-building, communication, and conflict-management skills just as purposefully and precisely as academic skills” (Johnson & Johnson, 1999, p. 71). In fact, for this approach to work, social skills cannot be viewed as an add-on but as a necessary component. Prater, Bruhl, and Serna (1998) express that “cooperative group social skills instruction should be the backbone of cooperative learning experiences” (p. 170). Elementary students may need explicit instruction in turn taking and sharing, whereas older students may need to learn how to accept mistakes, consider multiple perspectives, and engage in active listening (Mitchell et al., 2008; Prater et al., 1998). Finally, groups must engage in reflection about how and if they achieved their behaviour and/or academic goals (Johnson & Johnson, 1999; Jolliffe, 2015). Group members must decide on helpful versus unhelpful behaviours and strategies, placing importance on the process, as well as the product. Cooperative learning is an inclusive approach as the social and academic skills often needed by those learners with learning disabilities and emotional-behavioural disorders are embedded for all learners.

Shifting Perspectives

While the benefits of cooperative learning are apparent for those with varying abilities and general education students alike, Siegel (2005) notes that successful implementation depends on the teacher’s expertise. Finding a compromise between cooperative learning and direct instruction approaches would allow for an effective shift in practice. Prater et al. (1998) found that the best way to teach the social skills required for cooperative learning was through direct instruction. Furthermore, from a behavioural psychology perspective, students can be reinforced for their effective use of social skills, albeit as a group rather than individually. Many direct instruction strategies could still be used, such as demonstrations, feedback, and scaffolding. Instead of an overall abandonment of the teacher’s current teaching style, a shift in thinking and structuring is required. For instance, the objectives at the start of the lesson could continue, albeit as group goals. Group work can continue but with explicit roles and positive interdependence elements added. A shift from individual to group assessment would occur. In fact, informal cooperative learning may already be occurring through think-pair-shares (Johnson & Johnson, 1999). A shift to formal cooperative learning is possible by intentionally planning heterogenous groups for a set timeframe to meet specific goals (Johnson & Johnson, 2009). Constantinou (2010) notes that “the main goal of cooperative learning is to take some of the teacher’s responsibility and progressively shift it to the students” (p. 35). Thus, the largest shift would be from a teacher-centered to a student-centered approach, but this occurs over time with the teacher still facilitating the learning as student demands increase (Constantinou, 2010; Hannon & Ratliffe, 2004; Malmgren, 1998; Topping, 2005). Presenting this as a complimentary approach may reduce initial feelings of resistance from the teacher. Furthermore, the psychologist can use direct instruction strategies to model how cooperative learning can be implemented. This compromise will allow for increased teacher comfortability and fidelity to the approach.

Developing Competency through Experience: Implementation of Cooperative Learning

Implementation of cooperative learning starts with intentionally planning the heterogenous small groups and their shared tasks (Bryant & Bryant, 2005). In this case scenario, the teacher will create small groups of six, ensuring that all group members will be present during the scheduled time as they all have a role to play (Bryant & Bryant, 2005; Hannon & Ratliffe, 2004; Malmgren, 1998). The social skill of decision-making will be demonstrated first, with the teacher using familiar explicit instruction approaches to teach the expected behaviour before the students are to apply it in their groups. The teacher can create a t-chart with specific rules and responsibilities (Bryant & Bryant, 2005; Grenier et al., 2005; Hannon & Ratliffe, 2004). For instance, the t-chart may outline what cooperative group work and the specific social skill should look and sound like or a breakdown of the various roles:   

My Job (Teacher) is to…Your Job (Students) is to…
create groups;provide resources and role options;present the task and objectives;monitor group work and answer questions; model social skill: decision-making; listen to group processing and reward group (Bryant & Bryant, 1998; Grenier et al., 2005; Hannon & Ratliffe, 2004; Johnson & Johnson, 1999; Johnson & Johnson, 2009; Malmgren, 1998; Topping, 2005).work collaboratively with your group;select and rotate through roles;accomplish the objectives as a group; ask questions first of your group and then of your teacher; model social skill: decision-making;engage in group processing and earn group rewards (Grenier et al., 2005; Hannon & Ratliffe, 2004; Johnson & Johnson, 1999; Johnson & Johnson, 2009; Kuntz et al., 2001; Topping, 2005).

It is important that students know about the reward system and that they will be rewarded as a group (Bryant & Bryant, 2005; Hannon & Ratliffe, 2004). In this scenario, a marble jar will be used wherein each group can earn marbles when they effectively make decisions and/or collectively meet or show growth towards the task objective. Once the group fills their marble jar or receives a pre-determined amount of marbles, they can exchange this for a preferred activity or item.

The task is then outlined for the students, starting with a familiar template or repeated strategy (Hannon & Ratliffe, 2004). Initially, the psychologist can assist the teacher by co-teaching the strategy and providing feedback about implementation. The Jigsaw strategy is a great approach that lends itself to positive interdependence and individual accountability. Students are put into cooperative learning groups to learn about one portion of a topic after the teacher introduces it (Kuntz et al., 2001; Kyndt et al., 2013). Then, each member of the initial group joins a new group to teach them about what they learned. Therefore, students ultimately learn from all their classmates. Since each student has the responsibility to teach a portion of the concept, individual accountability and positive interdependence is present. At times, there can be a team score at the end and there should always be time for group processing and reflection (Kuntz et al., 2001). Johnson and Johnson (2009) note how the Jigsaw strategy can reduce social loafing and overcompensation of group members. Furthermore, Jigsaw can be structured to have English as Additional Language speakers with bilingual and English-only speakers (Kuntz et al., 2001), making concepts and group discussion accessible to all.

In the Grade 7 Saskatchewan Physical Education Curriculum, outcome 7.1 involves students making a fitness plan that incorporates daily movement as it relates to flexibility, and cardiovascular and muscular endurance (Ministry of Education, 2009). Students learn to monitor their heart rates as they safely participate in physical activities, such as sit-ups, push-ups, and v-sits (Ministry of Education, 2009). After the teacher’s direct instruction about the task and safety objectives, students are placed in their cooperative groups, with each group focusing on brainstorming activities from one of the following areas: flexibility, cardiovascular endurance, and muscular endurance. Then, using the Jigsaw approach, group members will shift allowing for a person from each cooperative homegroup in the new formations. In this second formation, students teach each other what they have learned in their cooperative homegroups. Finally, students go back to their cooperative homegroups to relay the most important thing that they learned and make an exercise list. They reflect upon what went well in the process using the ‘Stop/Start/Continue’ graphic organizer to chart specific behaviours and objectives.

The next day, students are in the gymnasium and back with their cooperative homegroups. The teacher shows the students how to monitor their heart rates before and after the warmup laps. Students are then put into their cooperative homegroups and assigned roles: motivator, heart rate monitor, recorder, participant, videographer, and safety patrol. Students take turns rotating through each role (Bryant & Bryant, 1998; Grenier et al., 2005; Hannon & Ratliffe, 2004; Johnson & Johnson, 1999; Johnson & Johnson, 2009). While they are the participant, students engage in exercises from the previous lesson. Students decide together if each exercise targets cardiovascular endurance, muscular endurance, flexibility, or a combination of two or more areas. Meanwhile, the teacher monitors and encourages participation and appropriate social skill use, particularly effective decision-making. To promote individual accountability, students are randomly called upon to discuss what they learned and which activities resulted in higher heart rates. Furthermore, students are asked at random which skill fits under cardiovascular endurance, muscular endurance, or flexibility and the teacher charts this on a classroom poster. The teacher asks students to go back to their collaborative homegroups and discuss if they met their social decision-making goal and their academic goal of classifying exercises. Students discuss what helpful and unhelpful behaviours were observed using the ‘Stop/Start/Continue’ graphic organizer. They collectively plan and set group goals for the next day.

Sustaining Practice: Implementation of Cooperative Learning in Math  

As the teacher gains competency, they can implement cooperative learning practices in additional classes. In math class, students are working on outcome 7.1 which focuses on divisibility strategies (Ministry of Saskatchewan, 2007). The teacher employs the Team Assisted Instruction (TAI) cooperative learning strategy. For this strategy, students work in heterogenous, cooperative groups but on individualized math units (Kuntz et al., 2001; Salvin, 1984). This allows for the benefits of cooperative learning to occur but accounts for the reality that students will be at different instructional levels (Kuntz et al., 2001; Salvin, 1984). In this scenario, some learners may be working on one- by one-digit division, while others are working on two- or three-digit division. Heterogenous groups allow students to learn from those at various levels and provide students with additional opportunities to discuss concepts and solidify their knowledge (Jenkins et al., 2003; Johnson & Johnson, 2009; Malmgren, 1998). Students are put into heterogenous teams and then take a placement test to determine what unit they will start on. The teacher circulates to each group for 15-minute individualized lessons and the students help each other with understanding instructions and determining the correct answers for the units they are on (Salvin, 1984). All students, regardless of level, can help each other because answer keys are provided (Salvin, 1984). Furthermore, promotive interaction can occur if roles are assigned, such as timekeeper, corrector, material collector, etc. (Johnson & Johnson, 2009). In addition to their group role, students work on their unit, which consists of an instruction sheet, worksheets, checkout questions, and a final test to determine mastery (Salvin, 1984).

The teacher can still utilize direct instruction, immediate feedback, and whole class lessons and quizzes as necessary (Salvin, 1984). However, Bryant and Bryant (2005) note that “peers can provide instruction and feedback more often than teachers can provide individual assistance to students who require it” (p. 41). Adaptations can be offered to all learners within a group, such as assistive technology, alternative forms of assessment, and scribes (Bryant & Bryant, 1998; Malmgren, 1998). This helps to reduce the barriers that students with disabilities may face, while normalizing and making adaptations available to all learners. Furthermore, “students learn to respect and accept one another’s strengths and limitations” (Constantinou, 2010, p. 35). Kuntz et al. (2001) report that “students with mild learning disabilities produced more accurate work in mathematics with cooperative learning over individual instruction” (p. 49). TAI allows for an inclusive, yet individualized approach to cooperative learning that benefits all students.

Positive interdependence occurs with TAI, as teams are rewarded as a group based on the average amount of units that they achieve and the individual improvements that they make (Kuntz et al., 2001; Salvin, 1984). Thus, if all members increase their score on individual tests and assignments, then the group is rewarded (Malmgren, 1998). Since everyone works at their own level, they have equal opportunities to earn rewards for their group (Salvin, 1984). Students can also be rewarded for effective group processes and use of social skills so that individual ability is not penalized or viewed as a liability to the group (Grenier et al., 2005). While individual marks are not shared with the group, individual improvements are charted (Kyndt et al., 2013) and students can collectively earn marbles like they did in physical education. Jenkins et al. (2003) note that teachers often fail to share individual performance with the group, which negatively impacts group accountability and positive interdependence. Johnson and Johnson (2009) recommend that “the performance of each individual member is assessed and the results are given back to the individual and the group to compare against a standard of performance” (p. 368). Thus, the TAI collaborative learning method allows for both individual accountability and positive interdependence, while fostering group processing, social skills, and promotive interaction.


Bridging perspectives can be accomplished through Jolliffe’s (2015) model. Educational psychologists can help teachers progress from a theoretical basis to increased competency and sustained learning in new teaching methods (Jolliffe, 2015). With a few intentional instructional and structural shifts, teachers can employ cooperative learning in their inclusive classrooms, while still drawing from their own expertise. Differing perspectives can be acknowledged as strengths and opportunities to compromise, which is what we would suggest to students engaging in collaborative learning. Goor and Schwenn (1993) define cooperative learning as “a set of instructional strategies that encourages cooperative student-student interactions in collectively and individually achieving lesson objectives” (p. 7). Cooperative learning offers many benefits from increased productivity, time on-task, and outcome achievement (Johnson & Johnson, 1999). Students learn valuable social skills, such as repair strategies, labour division, and perspective taking, all while making and maintaining peer friendships (Hannon & Ratliffe, 2004; Johnson & Johnson, 1999; Kuntz et al., 2001). Johnson & Johnson (1999) note that “when individuals work together to complete assignments, they interact (improving social skills and competencies), promote each other’s success (gaining self-worth), and form personal as well as professional relationships (creating the basis for healthy social development)” (p. 73). Cooperative learning is a socio-cultural psychology practice that increases academic and social skills for all learners in inclusive classrooms.

Works Referenced

Archer, A., Hughes, C., & Ebrary, I. (2011). Explicit instruction: Effective and efficient teaching. New York: Guilford Press.

Bryant, D. P., & Bryant, B. R. (1998). Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities. Journal of Learning Disabilities, 31(1), 41-54.

Constantinou, P. (2010). Keeping the excitement alive: Tchoukball and cooperative learning. Journal of Physical Education, Recreation & Dance, 81(3), 30-35.

Goor, M. B., & Schwenn, J. O. (1993). Accommodating diversity and disability with cooperative learning. Intervention in School and Clinic, 29(1), 6-16.

Grenier, M., Dyson, B., & Yeaton, P. (2005). Cooperative learning that includes students with disabilities. Journal of Physical Education, Recreation & Dance, 76(6), 29-35.

Hannon, J. C., & Ratliffe, T. (2004). Cooperative learning in physical education. Strategies: A Journal for Physical Education and Sport Educators, 17(5), 29-32.

Hollingsworth, J., & Ybarra, S. (2009). Explicit direct instruction (EDI): The power of the well-crafted, well-taught lesson. Thousand Oaks, California: Corwin Press Data Works Educational Research.

Jenkins, J. R., Antil, L. R., Wayne, S. K., & Vadasy, P. F. (2003). How cooperative learning works for special education and remedial students. Exceptional Children, 69(3), 279-292.

Johnson, D. W., & Johnson, R. T. (1999) Making cooperative learning work. Theory into Practice, 38(2), 67-73.

Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38(5), 365-379.

Jolliffe, W. (2015). Bridging the gap: Teachers cooperating together to implement cooperative learning. Education 3-13, 43(1), 70-82.

Kuntz, K. J., McLaughlin, T. F., & Howard, V. F. (2001). A comparison of cooperative learning and small group individualized instruction for math in a self-contained classroom for elementary students with disabilities. Educational Research Quarterly, 24(3), 41-56.

Kyndt, E., Raes, E., Lismont, B., Timmers, F., Cascallar, E., & Dochy, F. (2013). A meta-analysis of the effects of face-to-face cooperative learning: Do recent studies falsify or verify. Educational Research Review, 10(1), 133–149.

Malmgren, K. W. (1998). Cooperative learning as an academic intervention for students with mild disabilities. Focus on Exceptional Children, 31(4), 1-8.

Ministry of Education (2007). Grade Seven Mathematics Curriculum. Saskatchewan Curriculum. Retrieved from:

Ministry of Education (2009). Grade Seven Physical Education Curriculum. Saskatchewan Curriculum. Retrieved from:

Mitchell, M. G., Montgomery, H., Holder, M., & Stuart, D. (2008). Group investigation as a cooperative learning strategy: An integrated analysis of the literature. Alberta Journal of Educational Research, 54(4), 388-395. 

Prater, M. A., Bruhl, S., & Serna, L. A. (1998). Acquiring social skills through cooperative learning and teacher-directed instruction. Remedial and Special Education, 19(3), 160-172.

Salvin, R. E. (1984). Team assisted individualization: Cooperative learning and individualized instruction in the mainstreamed classroom. Rase, 5(6), 33-42.

Siegel, C. (2005). Implementing a research-based model of cooperative learning. The Journal of Educational Research, 98(6), 339-349.

Topping, K. (2005). Trends in peer learning. Educational Psychology: An International Journal of Experimental Educational Psychology, 25(6), 631-645.

Best Practices: Fetal Alcohol Spectrum Disorder (FASD)

By: Kourtney J. Gorham at The University of Regina for EPSY 821 – Aptitude and Achievement Analysis (Instructor Rori Lee)

Best Practices: Fetal Alcohol Spectrum Disorder (FASD)

Introduction: FASD Definition, Symptoms, and Prevalence

According to the FASD Network of Saskatchewan (2017) and the Canadian FASD Research Network (2019), Fetal Alcohol Spectrum Disorder (FASD) is a lifelong disability caused by prenatal alcohol exposure (PAE) that can impact an individual’s behavioral, cognitive, physical, and sensory domains. FASD has both neurocognitive and neurobehavioral implications, as PAE damages the Central Nervous System (CNS) in the developing fetus (Brown, Connor, Adler, and Langton, 2012; Nash & Davies, 2017; Popova, Lange, Burd, & Rehm, 2015). While specific impairments may not be realized until later in life when environmental demands increase, challenges with fine and gross motor skills, daily living skills, physical and mental health, learning, memory, executive functioning, receptive communication, social skills, and self-regulation may occur (Brown et al., 2012; CanFASD, 2019; FASD Network, 2017; Kully-Martens et al., 2018). However, each individual will experience different strengths and challenges and thus, requires individualized supports to target their unique areas of need.

FASD often goes undiagnosed due to stigma, lack of awareness, and the fact that it is an invisible disability as many individuals have no physical markings (FASD Network, 2017; Nash & Davies, 2017). Furthermore, FASD may be misdiagnosed as it commonly co-occurs with Attention Deficit Hyperactive Disorder (ADHD) – 40-90% of cases (Glass et al., 2017), Autism Spectrum Disorder (ASD), Bipolar Disorder (BD), Major Depressive Disorder (MDD), Intellectual Developmental Disorder (IDD), Oppositional Defiance Disorder (ODD), Reactive Attachment Disorder (RAD), Specific Learning Disability (SLD) – 17-35% of cases (Glass et al., 2017), and other sensory and trauma-related concerns (FASD Network, 2017; Nash & Davies, 2017). This is problematic because appropriate supports may not be in place without appropriate diagnosis.

FASD impacts individuals from all socioeconomic classes and ethnic groups and is especially apparent in cultures where alcohol is culturally accepted. The FASD Support Network (2017) notes that, “in Saskatchewan, it is believed that 1 in 100 people may be affected by FASD” (p. 4). CanFASD (2019) reports that “4% or 1.4 million people in Canada have FASD” (n.p.). These high rates may occur because approximately half of all pregnancies are unplanned (Nash & Davies, 2017) and there is no known safe amount or time to consume alcohol when pregnant (CanFASD, 2019; FASD Network, 2017; Osterman, 2011; Zizzo & Racine, 2017), including during the first month when individuals may not be aware of their pregnancy.  Statistics show that, on average, 90% of women abstain from drinking alcohol during pregnancy (Kully-Martins et al., 2018; Nash & Davies, 2017; Singal et al., 2017). However, social inequalities, lack of awareness, and previous addictions may contribute to continued use in some cases (Migliorini et al., 2015), making PAE a societal reality.

Overall fetal development is impacted by the quantity and timing of alcohol exposure, maternal metabolism rate, and the overall nutritional status of the mother (Brown et al., 2012; Kalberg & Buckley, 2007). Thus, not all individuals who have been prenatally exposed to alcohol will be diagnosed with FASD and presentations vary among those with the diagnosis (Brown et al., 2012; Kalberg & Buckley, 2007). Individual profiles may differ because neuroanatomical changes in the brain interact with the person’s environment to produce behaviors, particularly social deficits (Kully-Martens, Denys, Treit, Tamana, & Rasmussen, 2012). Within the behavioral domain, dysmaturity, issues interpreting social cues, and low self-esteem may occur (FASD Network, 2017; Kully-Martens et al., 2012). Brown et al. (2012) note that individuals with FASD are susceptible to peer pressure due to impulsivity, executive functioning deficits, and issues making, selecting, and retaining positive friendships. Cognitive impairments may include short attention spans, failure to learn from mistakes, and struggling to sequence behavior to reach a goal (executive functioning) (FASD Network, 2017; Kalberg & Buckley, 2007). Within the physical and sensory domains, poor balance and coordination, sensory processing concerns, and failure to meet height and weight developmental milestones may occur (FASD Network, 2017). These symptoms, and many more, can lead to secondary challenges such as unemployment, addictions, run-ins with the law, underachievement, difficulty learning advanced concepts, and school-drop out (FASD Network, 2017; Popova et al., 2015). In fact, individuals with FASD are 19 times more likely to go to jail (Popova et al., 2015), this being amplified if their needs are unmet, early diagnosis did not occur, and environmental concerns are present (Brown et al., 2012). While there is no cure for FASD, treatment to reduce secondary concerns is crucial.

Diagnosing FASD

 A multidisciplinary team of specialists is required to make a FASD diagnosis (Birch, Carpenter, March, Mcclung, & Doll, 2016; Cook et al., 2016; FASD Network, 2017). This team may include a specially trained physician, an educational and/or clinical psychologist or social worker, a speech language pathologist, an occupational therapist, a psychiatrist, and/or a pediatrician (FASD Network, 2017). Furthermore, once a diagnosis is made, treatment planning may include referrals to other specialized service providers. Brown et al. (2012) recommend a minimum of three professionals including a neuropsychologist to do the comprehensive testing, a medical doctor to conduct a physical examination, and a psychologist to administer psychological assessments, observe the child in multiple environments if possible, and interview and integrate information from all applicable sources, such as caregivers and birth records (Coons-Harding, Flannigan, Burns, Rajani, & Symens, 2019; Kalberg & Buckley, 2007; Sattler, 2014).

A FASD diagnosis requires three significant deficits at least 1 standard deviation (SD) below the mean in at least three neurocognitive domains and/or global IQ deficits (Brown, Connor, & Adler, 2012). Typically impairments must be below the third percentile (Coons-Harding et al., 2019). In addition to this, facial features, growth delays, and CNS functional, structural, and neurological damage may be apparent (Brown et al., 2012; Walker, Edwards, & Herrington, 2016). The FASD Network (2017) describes three diagnoses on the FASD spectrum: FASD with sentinel facial findings, FASD without sentinel facial findings, and at risk for neurodevelopmental disorder and FASD. To diagnosis FASD with sentinel facial findings there must be three facial features and three domains of impairment but PAE does not need to be confirmed (FASD Network, 2017). The facial features include “a thin upper lip, short palpebral fissure (the opening between eye lids), and smooth/flattened philtrum (the groove between the nose and lip)” (FASD Network, 2017, p. 6). In the second type, three domains of impairment remain but facial features are not required. In the absence of facial features, PAE must be confirmed (FASD Network, 2017). The at risk designation involves three facial features or PAE confirmed and a clinical concern about development (FASD Network, 2017).

Unfortunately, there are many barriers to receiving a diagnosis such as long waitlists, lack of service providers for all age groups, social inequalities such as transportation or rural access difficulties, lack of education and understanding, and persisting stigmatization of mothers (Chamberlain, Reid, Warner, Shelton, & Dawe, 2016; FASD Network, 2017).  In Saskatchewan we currently do not have a specially trained physician to identify short palpebral fissures, making FASD with sentinel facial findings hard to diagnose (FASD Network, 2017). For children, diagnosis and assessment services can be acquired through Child and Youth Services centers in Prince Albert, Saskatoon, and Regina. Adults can be referred to Child and Youth Services in Regina, Dr. Gerald Block in northern and central Saskatchewan, or the Saskatoon Genetics/Teratology Clinic at the Royal University Hospital in Saskatoon (Government of Saskatchewan, 2019). Supports, with or without diagnosis, can be obtained from the FASD Support Network of Saskatchewan and Raising Hope/Regina Street Worker’s Advocacy Program. Furthermore, caregivers and educators can consult the Best Practices for Serving Individuals with Complex Needs: Guide and Evaluation Toolkit (2018) by the Alberta Clinical and Community-Based Evaluation and Research Team and the FASD Prevention Framework (2014) from the Saskatchewan Prevention Institute.

FASD Diagnostic Tools

A variety of tools are used to asses FASD: the FASD Behavioral Mapping Tool to assess dysmaturity (FASD Network, 2017); the Fetal Alcohol Behavioral Scale that screens for 36 behaviors under the communication, emotional, social skills, academic, motor skills, and functional domains (Brown et al., 2012); and the FASD 4-Digit Diagnostic Code to assess the key diagnostic features (Walker et al., 2016). In addition, a battery of psychological tests and observations are used to look at domain-specific impairments in one or more of the following areas: motor skills, cognition, language, academic achievement, memory (verbal, auditory, and spatial), attention, executive functioning, affect recognition, and adaptive behavior (social skills and communication) (Brown et al., 2012; Kalberg & Buckley, 2007). Kalberg and Buckley (2007) note that an individual’s overall IQ score matters less than their ability to function within their environment, making a complete battery of assessments and observations essential.

Domain-specific assessments vary but should follow the Canadian FASD Research Network’s 2015 guidelines, with direct measures being preferred (CanFASD, 2019; Coons-Harding et al., 2019). Coons-Harding et al. (2019) surveyed 23 FASD clinics in Alberta to determine the comprehensive battery of neuropsychological tests that were being used. In some instances, assessments that were not recommended in the 2015 guidelines and older test editions were used. However, the following list includes the best practice measures that were used under each domain, with the first assessment in the list being used more frequently than the last (Coons-Harding et al., 2019, p. 45-9):

  1. Motor Skills Domain: Bruininks-Oseretsky Test of Motor Proficiency – 2nd Edition; Beery-Buktenica Developmental Test of Visual-Motor Integration – 6th Edition; Grooved Pegboard/Purdue Pegboard Test; Finger Tapping/Oscillation Test; Hand Dynamometer/Hand Grip Strength Test; Peabody Developmental Motor Scales – 2nd Edition; Miller Function and Participation Scales and Movement Assessment Battery for Children – 2nd Edition for caregiver interviews
  2. Cognitive Domain: Wechsler Adult Intelligence Scale – 3rd Edition; Wechsler Intelligence Scale for Children – 5th Edition; and Wechsler Preschool and Primary Scale of Intelligence – 4th Edition  
  3. Language Domain: Peabody Picture Vocabulary Test – 4th Edition; Clinical Evaluation of Language Fundamentals – 5th Edition; Test of Narrative Language – 2nd Edition; Expressive Vocabulary Test – 2nd Edition; Preschool Language Scales – 5th Edition; Perceptive-Expressive Emergent Language Test – 3rd Edition; Renfrew Bus Story; and language samples
  4. Academic Achievement Domain: Wechsler Individual Achievement Test – 3rd Edition; Woodcock Johnson Tests of Achievement – 4th Edition; Wide Range Achievement Test – 4th Edition
  5. Memory Domain: California Verbal Learning Test – 2nd Edition; Rey Complex Figure Test and Recognition Trial; Wide Range Assessment of Memory and Learning – 2nd Edition; NEPSY-II Subtests; Wechsler Memory Scale Revised – 4th Edition; Children’s Memory Scale
  6. Attention Domain: Connors – 3rd Edition and Adult ADHD Rating Scales; Behavior Assessment System for Children – 3rd Edition; Connors Continuous Performance Test –3rd Editions; and observations, anecdotal evidence, and reports from educators/caregivers
  7. Executive Function Domains: Behavior Rating Inventory of Executive Functioning – 2nd Edition; NEPSY-11; Delis-Kaplan Executive Function System; Test of Problem Solving – 2nd Edition (Adolescent) and 3rd Edition (Children); Wechsler Working Memory Scales; Wisconsin Card Sort Task; Behavior Assessment System for Children – 3rd Edition; Rey Complex Figure Test/Rey-Osterreich Complex Figure
  8. Affect Recognition Domain: Behavior Assessment System for Children – 3rd Edition; Beck Depression Inventory – 2nd Edition; Beck Anxiety Inventory; and previous/current diagnosis
  9. Adaptive Behavior (Social Skills and Communication) Domain: Adaptive Behavior Assessment System – 3rd Edition; Social Language Development Test; Vineland Adaptive Behavior Scales – 3rd Edition

FASD Best Practice Supports                                                                            

Supports for FASD generally fall under the best practice realm, as many of the strategies are general or have not been researched enough to be deemed evidence-based. This is further complicated by misdiagnosis, underdiagnoses, comorbid conditions, resource gaps for certain ages, and the variability of FASD presentations (FASD Network, 2017; Griffin & Copeland, 2018; Olson, 2016). The Alberta Clinical and Community-Based Evaluation and Research Team outlined supports with expert consensus, good evidence, moderate evidence, and some evidence in Practices for Serving Individuals with Complex Needs: Guide and Evaluation Toolkit (2018). Strategies with expert consensus included transition-focused supports and future planning, staff education, trauma supports, interpersonal skills, age-appropriate services, consistency and structure, Functional Behavior Assessments (FBA), preventative medical and mental health care, supported recreational activities, managing sexually exploitative situations and risky behaviors, person-centered employment, financial aid and access support, support with the justice system, and individualization. Supports with good evidence included early diagnosis, focusing on caregiver wellbeing, stable home environments, consistency, collaboration, responsiveness, and proactivity. Supporting sensory processing, utilizing unique learning profiles, parent-assisted adaptive functioning training and other educational resources had moderate evidence. Individual support, agency collaboration, strengths-based approaches, and secure and safe housing had some evidence (Pei, Tremblay, Poth, Hassar, & Ricioppo, 2018). Similarly, the FASD Network (2017) recommends general strategies in the areas of memory, confabulation, cause and effect, time management, transitions, ownership, impulse control, social skills, sensory, and sleep. Examples of strategies include repeating instructions in multiple ways, increasing time, and utilizing visuals (memory); probing only if it is a dangerous story and utilizing social stories (confabulation); utilizing positive reinforcement, visual reminders of expectations, and decision mapping (cause and effect); implementing timers, calendars, schedules, and predictable routines (time management); utilizing forewarning, prior practice. and visual schedules (transitions); practicing borrowing items and labelling personal belongings (ownership); implementing role-playing scripts, perspective taking, and supervision as needed (impulse control); modelling behavior, providing mentorship that builds off strengths, and setting developmentally appropriate expectations (social skills); reducing distractions, utilizing adaptive seating, and movement breaks (sensory); and implementing a calming sleep routine that may include doctor recommendations (sleep) (FASD Network, 2017). While the supports are general, they should be selected based on individual needs and strengths.

Specific programs for FASD have been created, however often with limited research or acceptable norm groups. The Children’s Friendship Training (CFT) program was created by the CDC Cooperative Research Group and combines child friendship training with parental education. Children learn how to enter play, interact with peers, and resolve conflicts during 12 weekly 90-minute sessions. Techniques such as role play, homework assignments, and caregiver play coaching are used (Brown et al., 2012). Olson (2016) reported immediate positive “effects on social knowledge and skills, and problem behavior” (p. 1819) and Brown et al. (2012) noted that these positive gains were maintained three months later.

The Math Interactive Learning Experience (MILE) also has been shown to be effective with results lasting after six months (Kable, Taddeo, Strickland, & Coles, 2015; Kully-Martens et al., 2017). It was created by Kable in 2007 and piloted to 61 children ages three to ten in Georgia. In the program, students receive six weeks of one-on-one math instruction that is individualized based on their baseline data and includes interactive and physical exploration of objects, slower instruction, immediate feedback on errors, and metacognition techniques for problem solving through the Plan-Do-Review model or Focus-Act-Reflect (FAR) mnemonic. Parents receive six weeks of training. In Kable et al.’s (2015) self-report study, students had learned twelve new math concepts vs. three in the control group after two months but it was a small sample size and the parental piece may not have had any impact. In a Canadian study with 28 children ages four to ten, those who were older with confirmed PAE but no FASD diagnosis, and lower IQs made greater gains with MILE (Kully-Martens et al., 2018).

Additional programs are available for specific areas of need. Caribbean Quest is a computer program that targets attention and working memory and MacSween et al. (2015) note that the program led to significant improvements with auditory, visual, and working memory. The GoFar program aims to improve self-regulation and adaptive skills through computerized games, parent training, and the FAR mnemonic (Kable, Taddeo, Strickland, & Coles, 2016). The program occurs over ten weeks with phase one focusing on learning the FAR technique and phase two focusing on application of the strategy. It has online and in-person parent training options (Kable et al., 2016). However, the sample size was small and little research about the effectiveness is available.  Parents Under Pressure (PuP) focuses on self-regulation and mindfulness through the child-parent relationship (Reid et al., 2017). This program has preliminary support because there was a small sample size and issues with accurately measuring growth. It was built on the foundation “that self-regulation underpins adaptive functioning” (Reid et al., 2017, p. 46). Project Step Up promotes parental education and harm-reduction for youths with FASD using substances. It has satisfactory results for those with IQs over 70 but success may actually be attributed to supportive home environments (O’Connor, Quattlebaum, Castaneda, & Dipple, 2016; Olson, 2016). Step-by-Step is a one-on-one mentorship program for parents affected by FASD. It assists individuals with socioeconomic disadvantages but little research is available (Denys, Rasmussen, & Henneveld, 2011). While there are many available programs, continued research is needed to determine which programs can be considered evidence-based strategies.


While there is no cure for FASD, targeted intervention and remediation of secondary concerns is promising. Medications are sometimes used to target comorbid conditions (Brown et al., 2012; Nash & Davies, 2017) but additional research is needed as stimulant medications have controversial results and may increase heart problems and seizures in this population (Brown et al., 2012) . Pei et al. (2017) note that recommendations made most to least are:  “education, medical, anticipatory guidance, accommodations, family support, mental health, developmental therapy, social services/child welfare, community/social/leisure programs, safety, reassessment, and other” (p. 176). However, they found that recommendations may be based on comorbid disorders or availability in the community rather than individualized need. Brown et al. (2012) recommend that no matter what program or strategy is used, the focus should be on replacing maladaptive behaviors. Additional research on strategies and programs for individuals with FASD will help determine evidence-based supports. Providing the subsequent supports and services to all those impacted by FASD is paramount in remediating lifelong secondary concerns and helping individuals be as successful as they can be.

Works Referenced

Birch, S., Carpenter, H., Marsh, A., Mcclung, K., & Doll, J. (2016). The knowledge of rehabilitation professionals concerning fetal alcohol spectrum disorders. Occupational Therapy In Health Care, 30(1), 69-79.

Brown, N., Connor, P., Adler, R., & Langton, C. (2012). Conduct-disordered adolescents with fetal alcohol spectrum disorder: Intervention in secure treatment settings. Criminal Justice and Behavior, 39(6), 770-793.

CanFASD: Canada FASD Research Network (2019). Diagnosis.Retrieved from:

Chamberlain, K., Reid, N., Warner, J., Shelton, D., & Dawe, S. (2017). A qualitative evaluation of caregivers’ experiences, understanding and outcomes following diagnosis of FASD. Research in Developmental Disabilities, 63(C), 99-106.

Cook, J. L., Green, C. R., Lilley, C. M., Anderson, S. M., Baldwin, M. E., Chudley, A. E.,… Rosales, T. (2016). Fetal alcohol spectrum disorder: A guideline for diagnosis across the lifespan. Canada Fetal Alcohol Spectrum Disorder Research Network, 188(3), 191-7.  

Coons-Harding, K., Flannigan, K., Burns, C., Rajani, H., & Symens, B. (2019). Assessing for fetal alcohol spectrum disorder: A survey of assessment measures used in Alberta, Canada. Journal of Population Therapeutics and Clinical Pharmacology, 26(1), 39-55.

Denys, K., Rasmussen, C., & Henneveld, D. (2011). The effectiveness of a community-based intervention for parents with FASD. Community Mental Health Journal, 47(2), 209-219.

FASD Network of Saskatchewan Inc. (2017). Fetal alcohol spectrum disorder: A guide to awareness and understanding.

Glass, L., Moore, E., Akshoomoff, N., Jones, K., Riley, E., & Mattson, S. (2017). Academic difficulties in children with prenatal alcohol exposure: Presence, profile, and neural correlates. Alcoholism: Clinical and Experimental Research, 41(5), 1024-1034.

Government of Saskatchewan (2019). Fetal alcohol spectrum disorder services. Retrieved from:

Griffin, M., & Copeland, S. (2018). Effects of a self-management intervention to improve behaviors of a child with fetal alcohol spectrum disorder. Education and Training in Autism and Developmental Disabilities, 53(4), 405-414.

Kable, J., Taddeo, E., Strickland, D., & Coles, C. (2016). Improving FASD children’s self-regulation: Piloting phase 1 of the GoFAR intervention. Child & Family Behavior Therapy, 38(2), 124-141.

Kable, J. A., Taddeo, E., Strickland, D., & Coles, C. (2015). Community translation of the math interactive learning experience program for children with FASD.  Research in Developmental Disabilities, 39, 1-11.

Kalberg, W., & Buckley, D. (2007). FASD: What types of intervention and rehabilitation are useful? Neuroscience and Biobehavioral Reviews, 31(2), 278-285.

Kully‐Martens, K., Denys, K., Treit, S., Tamana, S., & Rasmussen, C. (2012). A review of social skills deficits in individuals with fetal alcohol spectrum disorders and prenatal alcohol exposure: Profiles, mechanisms, and interventions. Alcoholism: Clinical and Experimental Research, 36(4), 568-576.

Kully-Martens, K., Pei, J., Kable, J., Coles, C., Andrew, G., & Rasmussen, C. (2018). Mathematics intervention for children with fetal alcohol spectrum disorder: A replication and extension of the math interactive learning experience (MILE) program. Research in Developmental Disabilities, 78, 55-65.

Macsween, J., Kerns, K. A., Macoun, S., Pei, J., Hutchinson, M., Rasmussen, C., & Bartle, D. (2015). Investigating the efficacy of computerized cognitive intervention for children with FASD and ASD. International Journal of Developmental Neuroscience, 47, 13.

Migliorini, R., Moore, E., Glass, L., Infante, M., Tapert, S., Jones, K.,… Riley, E. (2015). Anterior cingulate cortex surface area relates to behavioral inhibition in adolescents with and without heavy prenatal alcohol exposure. Behavioural Brain Research, 292, 26-35.

Nash, A., & Davies, L. (2017). Fetal alcohol spectrum disorders: What pediatric providers need to know. Journal of Pediatric Health Care, 31(5), 594-60.

O’Connor, M., Quattlebaum, J., Castañeda, M., & Dipple, K. (2016). Alcohol intervention for adolescents with fetal alcohol spectrum disorders: Project step up, a treatment development study. Alcoholism: Clinical and Experimental Research, 40(8), 1744-1751.

Olson, H. (2016). A renewed call to action: The need for systematic research on interventions for FASD. Alcoholism: Clinical and Experimental Research, 40(9), 1817-1821.

Osterman, R. (2011). Decreasing women’s alcohol use during pregnancy. Alcoholism Treatment Quarterly, 29(4), 436-452.

Pei, J., Baugh, L., Andrew, G., & Rasmussen, C. (2017). Intervention recommendations and subsequent access to services following clinical assessment for fetal alcohol spectrum disorders. Research in Developmental Disabilities, 60, 176-186.

Pei, J., Tremblay, M., Poth, C., Hassar, B. E., & Ricioppo, S. (2018). Best Practices for Serving Individuals with Complex Needs: Guide and Evaluation Toolkit. PolicyWise for Children and Families in collaboration with the University of Alberta. Retrieved from:

Popova, S., Lange, S., Burd, L., & Rehm, J. (2015). Cost attributable to fetal alcohol spectrum disorder in the Canadian correctional system. International Journal of Law and Psychiatry, 41, 76.

Reid, N., Dawe, S., Harnett, P., Shelton, D., Hutton, L., & O’Callaghan, F. (2017). Feasibility study of a family-focused intervention to improve outcomes for children with FASD. Research in Developmental Disabilities, 67, 34-46.

Saskatchewan Prevention Institute. Fetal alcohol spectrum disorder (FASD) prevention framework (2014). Government of Saskatchewan.

Sattler, J. (2014). 6th Ed. Foundations of behavioral, social, and clinical assessment of children. La Mesa, California: Jerome M. Sattler, Publishers, Inc.

Singal, D., Brownell, M., Chateau, D., Hanlon-Dearman, A., Longstaffe, S., & Roos, L. (2017). The psychiatric morbidity of women who give birth to children with fetal alcohol spectrum disorder (FASD): Results of the Manitoba mothers and FASD study. The Canadian Journal of Psychiatry, 62(8), 531-542.

Walker, D. S., Edwards, W. E., & Herrington, C. (2016). Fetal alcohol spectrum disorders: Prevention, identification, and intervention. The Nurse Practitioner, 41(8), 28-34.

Zizzo, N., & Racine, E. (2017). Ethical challenges in FASD prevention: Scientific uncertainty, stigma, and respect for women’s autonomy. Canadian Journal of Public Health, 108(4), 414-417.

Anatomical and Physiological Changes to the Brain Due to Prenatal Alcohol Exposure (PAE)

By: Kourtney J. Gorham at The University of Regina for EPSY 836 – Neuropsychology  (Instructor Louise Burridge)

Anatomical and Physiological Changes to the Brain Due to Prenatal Alcohol Exposure (PAE)


Alcohol is a teratogen that has detrimental effects on the developing fetus, often causing anatomical and physiological changes to the brain. When a pregnant mother consumes alcohol, it enters through the placenta and impacts fetal development through cellular and structural impairments (Brown, Connor, Adler, & Langton, 2012; Lebel, Roussotte, & Sowell, 2011). According to Nash and Davies (2017), the fetus’s blood-alcohol level matches the mother’s blood-alcohol level after an hour or two. However, due to reuptake of amniotic fluid, the blood-alcohol level can remain high for longer (Nash & Davies, 2017). Additional factors such as the mother’s metabolism and health, the amount of alcohol consumed, the frequency of consumption, and the point in fetal development when the insult occurred all contribute to overall fetal health (Brown et al., 2012; Kolb, Whishaw, & Teskey, 2019; Nash & Davies, 2017). It is generally agreed that the first trimester – particularly during the second through eighth weeks when the brain structures start to form and DNA synthesis occurs – is a critical time period when the effects of alcohol can be quite damaging (Brown et al., 2012; Kolb et al., 2019; Saskatchewan Prevention Institute, n.d.). For instance, Lebel et al. (2011) found that facial dysmorphology likely occurs when alcohol is consumed during the third and fourth weeks of fetal development. However, there is no safe time or safe level of alcohol to consume during pregnancy (CanFASD, 2019; FASD Network of Saskatchewan [FASD Network], 2017; Osterman, 2011; Saskatchewan Prevention Institute, n.d.; Zizzo & Racine, 2017) and even one drink per day has been found to lower IQ levels (Nash & Davies, 2017). For researchers, caregivers, educators, healthcare providers, speech pathologists, occupational therapists, and psychologists alike, knowledge about the anatomical and physiological changes to the brain due to prenatal alcohol exposure (PAE) is crucial for implementing appropriate supports and interventions.

For four decades we have known about the harmful effects of alcohol on the developing fetus (Glass et al., 2017), yet insults still occur. PAE can lead to a diagnosis of Fetal Alcohol Spectrum Disorder (FASD) – a lifelong disability that can impact an individual’s behavioral, cognitive, physical, and sensory domains (CanFASD, 2019; FASD Network, 2017). FASD has both neurocognitive and neurobehavioral implications, as PAE damages the Central Nervous System (CNS) in the developing fetus (Brown et al., 2012; Nash & Davies, 2017; Gorham, 2019; Popova, Lange, Burd, & Rehm, 2015). In fact, Chen, Maier, Parnell, and West (2003) found that cognitive and behavioral challenges are caused by the CNS damage rather than Intelligence Quotient (IQ) or other contributing factors alone. Despite this general understanding, the Canada FASD Research Network [CanFASD] (2019) reports that prevalence rates of FASD are 4% or 1.4 million Canadians. At least 1% of individuals in Saskatchewan have FASD with many more going undiagnosed (FASD Network, 2017). This may be because approximately 50% of adult pregnancies and 80% of adolescent pregnancies are unplanned (Nash & Davies, 2017). Nash and Davies (2017) found that only 9.4% of adults and 13.4% of teenagers drank during pregnancy, with each trimester seeing a reduction in drinking behaviors. This is compared to the 50% of adult women and 22% of teenage girls that drank before pregnancy (Nash & Davies, 2017). Thus, many individuals cease alcohol use once aware of their pregnancy but social inequalities, lack of education, and previous addictions may contribute to continued use in some cases (Migliorini et al., 2015), making PAE a societal reality (Gorham, 2019).

While we have known prevalence rates, it can be hard to get exact information about the amount, frequency of use, and developmental time of insult. Deciphering between abnormalities in the brain caused by PAE versus comorbid diagnoses – such as Attention Deficit Hyperactivity Disorder (40-90% of cases) and Specific Learning Disorders (17-35% of cases) (Glass et al., 2017) – and/or other substances used prenatally further complicates research (Lebel et al., 2011). Factors such as maternal metabolism, nutrition, and genetics also are hard to account for and testing theories is often unethical, thus resulting in animal studies that do not always translate to humans (Brown et al., 2012; Nash & Davies, 2017). Furthermore, while diagnosis of FASD involves a combination of facial abnormalities, tenth percentile growth deficits, and structural and functional CNS abnormalities (Brown et al., 2012), differences in brain structure and presentation occurs among individuals with PAE but who may or may not meet formal diagnostic criteria (Brown et al. 2012; Nash & Davies, 2017). Various anatomical and physiological abnormalities due to PAE have been observed, with the following showing up most frequently in the literature: microcephaly, reduced white and gray matter volumes, malformations in the frontal, parietal, and temporal lobes, corpus callosum abnormalities, and neural loss and communication issues (Lebel et al., 2011).

Anatomical Abnormalities: Microcephaly and Reduced White and Gray Matter Volumes

Reduced head size, called microcephaly, and reduced brain size and volume has been found in those prenatally exposed to alcohol (Chen et al., 2003; Fryer et al., 2012; Lebel et al., 2011; Nash & Davies, 2017; Stephen et al., 2012). The effects can be exasperated by being prenatally exposed to smoking in addition to alcohol (Nash & Davies, 2017). According to the Center for Disease Control and Prevention [CDC] (2018), microcephaly can lead to developmental delays, seizures, cognitive impairments, hearing and vision problems, and general issues with movement and balance – presentations often found in those with PAE.

Neuroanatomical abnormalities such as reduced white and gray matter volumes have been found in those with PAE, even after accounting for microcephaly and reduced brain volumes overall (Lebel et al., 2011). White matter volumes are particularly abnormal in the right hemisphere (Lebel et al., 2011). Eckstrand et al. (2012) found that the white matter loss lends itself to structural dysmorphology. Furthermore, Chen et al. (2003) found reduced white matter volumes in the parietal lobe and cerebral cortex. This can cause complications such as an abnormal metabolic rate of the thalamus and decreased communication to parts of the brain, such as the caudate nucleus (Chen et al., 2003).

Gray matter regions such as the caudate nucleus, thalamus, amygdala, hippocampus, basal ganglia, putamen, and pallidum appear to be particularly vulnerable to the effects of PAE (Eckstrand et al., 2012; Fryer et al., 2012; Lebel et al., 2011; Sharma & Hill, 2017; Zhou et al., 2015). Studies have shown that these areas are smaller (Lebel et al., 2011; Sharma & Hill, 2017), with certain areas seeing volume reductions of three to eleven percent (Zhou et al., 2015). This has vast implications on the individual, as these regions are responsible for important tasks: species-related behavior, memories, and emotions (amygdala and hippocampus); spatial perception (hippocampus); sensory integration (thalamus); and voluntary movement, attention control, explicit and reinforced learning, reward salience, and cognitive control mediation (basal ganglia) (Fryer et al., 2012; Kolb et al., 2019). For instance, Lebel et al. (2011) found that hippocampal volume and verbal abilities have an inverse relationship. Furthermore, Fryer et al. (2012) found that a reduction of volume in the caudate nuclei predicted lower neuropsychological performance, even after IQ was controlled for. They found that there was a decreased amount of glucose being metabolized in the caudate nuclei, impacting responses during behavior inhibition tasks. The caudate nuclei help with cognitive control and verbal learning and recall (Fryer et al., 2012) so it makes sense that abnormalities in this area would impact cognitive performance. It has been proposed that there is a dose-dependent relationship between alcohol consumption and caudate and gray matter volumes (Eckstrand et al., 2012; Fryer et al., 2012), but the specific dose has yet to be determined.

Anatomical Abnormalities: Frontal, Parietal, and Temporal Lobes

While the occipital lobe is relatively spared by the effects of alcohol, the same cannot be said for the frontal, parietal, and temporal lobes (Eckstrand et al., 2012; Lebel et al., 2011). These areas of the brain are responsible for executive functioning, voluntary movement, decision-making (frontal lobe), goal-oriented movement (parietal lobe), and senses, language, emotional processing, and facial recognition (temporal lobe), among many other functions (Kolb et al., 2016). The frontal lobe in those with PAE contains less white and gray matter volume. The parietal and temporal lobes also have less white and gray matter volumes due to narrowness of the lobes (Lebel et al., 2011). Additional anatomical abnormalities include thicker cortices, reduced gyrification, less temporal asymmetry, and displacement of the inferior parietal and temporal regions (Lebel et al., 2011). The structural brain damage in these regions has been linked to issues in cognition (Lebel et al., 2011) and planning, initiating, and controlling voluntary movements (Nguyen, Levy, Riley, Thomas, & Simmons, 2013).

Infante et al. (2015) found that those with PAE had reduced gyrification – cortical folding in the brain to create sulci and gyri to promote neuron connections and efficiency. Increased gyrification lends itself to higher IQs because the brain is making connections efficiently (Infante et al., 2015). Cortical folding typically occurs in the third trimester but no time in fetal development is safe from the harmful effects of alcohol (Infante et al., 2015). The reduced gyrification in the frontal and temporal cortices may present as cognitive and behavioral challenges, while reduced gyrification in the parietal cortex may result in issues with working memory (Infante et al., 2015). It is important to note that reduced gyrification has been found in those with ADHD and can be hard to differentiate from PAE due to comorbidity. However, Sharma and Hill (2017) found that there was a dose-dependent relationship between alcohol use and temporal lobe fusiform gyrus decreases. Thus, PAE likely also plays a role in reduced gyrification.

Differences in overall cortical thickness were found, particularly in the frontal and parietal lobes (Infante et al., 2015; Lebel et al., 2011; Zhou et al., 2015). In typically developing children, cortical surface area decreases as a result of brain maturity and efficiency; however, in those with PAE, cortical thickness was observed (Moore et al., 2017). This may account for differences in verbal learning (Lebel et al., 2011). Glass et al. (2017) used the Wechsler Individual Achievement Test – Second Edition (WIAT-II) to compare those with PAE to a normative control group. Those with PAE performed worse, struggling most with high-order math skills followed by numerical operations, spelling, and word reading. Over half of the cases (58%) in the PAE group were at least one standard deviation (SD) from the mean on one or more academic domains. Math difficulties were a result of parietal lobe abnormalities and spelling difficulties were a result of temporal lobe abnormalities (Glass et al., 2017). Glass et al. (2017) attributed this cognitive discrepancy to atypical brain development, cortical abnormalities, and the structural changes that were observed with neuroimaging.

Anatomical and Physiological Abnormalities: Corpus Callosum

 A particular area of concern is the corpus callosum – the largest white matter tract of 200 million fibres that is primarily responsible for hemispheric communication (Jacobson et al., 2017). It connects the cerebral hemispheres and provides a direct route for communication (Lebel et al., 2011; Jacobson et al., 2017; Kolb et al., 2019). The corpus callosum connects the neocortical areas and has a role in sensory, motor, and high-order communication (Jacobson et al., 2017). It develops during the second trimester during weeks 18 to 20 and increases in size during the third trimester and two years postpartum (Jacboson et al., 2017). If an individual is developing as expected, the corpus callosum will efficiently communicate from one cerebral hemisphere to another (Roebuck, Mattson, & Riley, 2002).

However, alcohol impacts genetic expression in this area of the brain (Nash & Davies, 2017). Both the shape and location of the corpus callosum are abnormal and complete or partial agenesis may occur (Eckstrand et al., 2012; Jacobson et al., 2017; Sowell et al., 2001; Sharma & Hill, 2017; Stephen et al., 2012), as well as colossal thinning (Lebel et al., 2011). The complete or partial agenesis may be due to toxic levels of alcohol being exposed during time of development or repeated insults impacting growth (Sowell et al., 2001). Lebel et al. (2011) found that the corpus callosum had smaller volume, area, and length and the shape variability increased with higher PAE. Jacobson et al. (2017) found that the corpus callosum was smaller, even after accounting for age, sex, and other prenatal toxins. Sowell et al. (2011) found that the corpus callosum was seven millimetres away on average from where it was supposed to be, impacting verbal learning and connectivity. This displacement, more so than the size discrepancy, impacts verbal learning (Lebel et al., 2011; Sowell et al., 2001), as interhemispheric communication is impaired.

In addition, the anterior cingulate cortex (ACC) – that surrounds the front of the corpus callosum – has reduced volumes and size, particularly on the right side (Infante et al., 2015; Migliorini et al., 2015; Roebuck et al., 2002). Migliorini et al. (2015) found that this resulted in slower inhibition completion time on the NEPSY-II subtests. ACC abnormalities can be attributed to executive functioning impairments, as this part of the brain has a role in conflict and error monitoring and information processing (Migliorini et al., 2015).

Various studies have shown the negative impacts of corpus callosum abnormalities due to PAE. Jacobson et al. (2017) attributed lower overall IQs and difficulties with verbal comprehension and processing speed on the Wechsler Intelligence Scale for Children – Fourth Edition (WISC-IV) to abnormalities in the corpus callosum. The midline structures, such as the hippocampus, that communicate with the corpus callosum were impacted (Jacobson et al., 2017); they surmised that the lack of transfer due to midline structural impairments likely lead to the poorer performance by the PAE group (Jacobson et al., 2017). Furthermore, Donald et al. (2016) found that in the corpus callosum there was a white matter connectivity issue. Connectivity between the caudate and executive functioning networks was limited, impairing perceptual reasoning and thalamus connectivity. Roebuck et al. (2002) found that those with PAE made more errors when information had to cross the corpus callosum but fewer errors if information was uncrossed. Thus, tasks with increased complexity resulted in more frequent errors. The interhemispheric transfer was viewed through magnetic resonance imagining (MRI) and complications were related to abnormal corpus callosum size (Roebuck et al., 2002). They found that the displacement of the corpus callosum and ineffective processing between the two hemispheres led to cognitive and psychosocial impairments. Brown et al. (2012) attributed executive functioning deficits to corpus callosum malformation due to neural communication complications. In addition, colossal thinning has been connected to poor motor skills (Lebel et al., 2011; Roebuck et al., 2002). Thus, the presentations we see in those impacted by PAE may occur because of brain connectivity and communication issues.

Physiological Abnormalities: Neural Loss and Communication Issues

Functional abnormalities, such as cellular alternations and neural loss, can occur due to PAE (Chen et al., 2003; Eckstrand et al., 2012). Nash and Davies (2017) explain that the toxic byproducts left behind by alcohol – especially in individuals without the alcohol dehydrogenase enzyme that metabolizes alcohol – can lead to abnormal cell growth and division leading to neurological system abnormalities. In other words, alcohol disrupts cell growth and migration (Eckstrand et al., 2012). Issues in cell migration – often due to agenesis, poor myelination, poor axonal integrity, or thinning – complicate transmission to dendrites in the cortex, hippocampus, and other important brain structures (Jacobson et al., 2017; Migliorini et al., 2015). Thus, PAE impacts cell migration from the production to the end site, impacting cell communication (Chen et al., 2003). Chen et al. (2003) found that there are less dendrites for communication in general. They further explain that neural loss and cell communication difficulties can present as cognitive and behavioral concerns.


PAE has detrimental effects on the developing fetus that last a lifetime. While many parts of the brain are impacted, microcephaly, reduced white and gray matter volumes, malformations in the frontal, parietal, and temporal lobes, abnormalities in the corpus callosum, and neural loss and communication issues are of most concern (Lebel et al., 2011). These anatomical and physiological impairments have far-reaching effects in areas of verbal reasoning, motor functioning, global IQ, and social abilities. Lebel et al. (2011) state that reduced size of the hippocampus and corpus callosum correlates with the number of days spent drinking in a week while pregnant. Furthermore, the amount of alcoholic beverages consumed relates to frontal lobe, caudate nuclei, and hippocampus volume decreases (Lebel et al., 2011). However, additional research is required to further understand the brain abnormalities and their effects. Assessment, interventions, and supports for those with PAE should improve as we better understand the specific CNS impairments and how the environment exasperates these anatomical and physiological abnormalities.

Works Referenced

Brown, N., Connor, P., Adler, R., & Langton, C. (2012). Conduct-disordered adolescents with fetal alcohol spectrum disorder: Intervention in secure treatment settings. Criminal Justice and Behavior, 39(6), 770-793.

CanFASD: Canada FASD Research Network (2019). Diagnosis. Retrieved from:

Center for Disease Control and Prevention (CDC) (2018). Facts about microcephaly. Retrieved from:

Chen, W. A., Maier, S. E., Parnell, S. E., & West, J. R. (2003). Alcohol and the developing brain: Neuroanatomical studies. Alcohol Research & Health, 27(2), 174-80.

Donald, K., Ipser, J., Howells, F., Roos, A., Fouche, J., Riley, E.,… Stein, D. (2016). Interhemispheric functional brain connectivity in neonates with prenatal alcohol exposure: Preliminary findings. Alcoholism: Clinical and Experimental Research, 40(1), 113-121.

Eckstrand, K. L., Ding, Z., Dodge, N. C., Cowan, R. L., Jacobson, J. L., Jacobson, S. W., & Avison, M. J. (2012). Persistent dose‐dependent changes in brain structure in young adults with low‐to‐moderate alcohol exposure in utero. Alcoholism: Clinical and Experimental Research, 36(11), 1892-1902

FASD Network of Saskatchewan Inc. (2017). Fetal alcohol spectrum disorder: A guide to awareness and understanding.

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