Thursday, November 8, 2018

Relations Among Socioeconomic Status, Age, and Predictors of Phonological Awareness

McDowell, K. D., Lonigan, C. J., & Goldstein, H. (2007). Relations among socioeconomic status, age, and predictors of phonological awareness. Journal of Speech, Language, and Hearing Research, 50(4), 1079-1092.

There are many individual differences that influence a child’s ability to learn to read. For example, the ability to identify or manipulate sounds in words known as phonological awareness has been found to be strongly related to reading success. McDowell and colleagues consider why phonological awareness skills may differ across individuals by examining two hypotheses. First, the phonological deficit hypothesis which holds that children with poorly established phonological representations will have difficulty with phonological awareness tasks. The second is the lexical restructuring model which describes a child’s phonological awareness skill as a function of their vocabulary. In other words, as a child’s vocabulary grows, they develop more sophisticated spoken word recognition skills, and this allows them to break down a word which makes the phonemic units of the words more accessible. This study involved the examination of the extent to which phonological awareness skills were explained by performance on measures related to these two hypotheses (speech sound accuracy and vocabulary, respectively) as well as the child’s age and socioeconomic status.

Preschool participants between the ages of 2 and 5 years old completed a wide range of speech and language assessments to capture phonological awareness skill, vocabulary and speech sound accuracies. Results revealed that speech sound accuracy, vocabulary, SES, and age each contributed unique variance to the prediction of phonological awareness skill. The authors concluded that since speech sound accuracy and vocabulary both explained phonological awareness that these results support both the phonological deficit hypothesis and the lexical restructuring model. Further analyses revealed that age moderated the relationship between speech sound accuracy and phonological awareness.  These results indicated that as children get older the continued occurrence of speech sound inaccuracies more strongly predicts poor phonological awareness skills.

This research illustrates the complexity that individual differences bring to predicting a child’s ability to learn to read. Further, the results emphasize the need to build both vocabulary knowledge and good quality of phonological representations of known words.

Blogger: Meghan Vollebregt is a student in the combined SLP MClSc/PhD program working under the supervision of Dr. Lisa Archibald.

Tuesday, October 16, 2018

Sequential prediction of literacy achievement for specific learning disabilities contrasting in impaired levels of language in Grades 4 to 9

Sanders, E.A., Berninger, V.W., Abott, R.D. (2017). Sequential prediction of literacy achievement for specific learning disabilities contrasting in impaired levels of language in grades 4 to 9. Journal of Learning Disabilities, 51(2), 137-157.

Do you ever think about your thinking, and try to explain it? The process of ‘translating’ your cognitive or thinking skills using language (or linguistic representations) is known as cognitive-linguistic translation. Cognitive-linguistic translation has been associated with reading and writing outcomes in typically developing children, possibly because reading and writing place demands on both our cognitive and linguistic skills (Niedo et al., 2014).

Working memory refers to the ability to briefly store and manipulate information in mind. Working memory has also been found to be related to reading and writing achievement. This study considers a number of proposed subcomponents of working memory:

  • word-form coding, which involves storing and processing information about the sounds (phonology), written letters (orthography), and meaning units (morphology) of a word 
  • phonological loop, which stores the phonological forms of words, and is important in naming visual objects or reading words (orthographic forms) 
  • orthographic loop, which stores representations of written letters and words (orthography), enabling the sequential finger movements that are required for writing letters or words; 
  • supervisory attention and executive functions, which refers to the ability to focus (or regulate) attention to relevant information and switches the focus of attention as relevance changes.

The aim of the study was to examine the relationship between cognitive-linguistic translation and working memory subcomponents to reading and writing in children with specific learning disabilities, including dysgraphia (handwriting impairment), dyslexia (word reading and spelling impairment), and oral and written language impairment.

Children in grades 4 to 9 completed a large battery of achievement tests measuring multileveled reading, writing, and language achievement, to assign participants to the dyslexia, dysgraphia, and oral/written language impairment groups based on which group best characterized their specific learning disability. Participants also completed a number of tasks measuring cognitive-linguistic translation, word-form coding at the phonological, orthographic, and morphological levels, phonological loop, orthographic loop, and executive functions including focused attention and switching attention.

The authors used a sequential multiple regression to examine how working memory components and cognitive linguistic translation predicted academic achievement. The results showed that while cognitive-linguistic translation accounted for a significant percentage of variation in reading and writing achievement, all of the working memory components accounted for additional unique variance in reading and writing achievement. With respect to writing achievement, a lower percentage of variance was accounted for by the predictor variables, relative to reading achievement. When a variable coding group membership was added to the regression model, there was a small percentage of variance accounted for, suggesting that there are some additional differences in learning disability profiles beyond what was captured by cognitive-linguistic translation and working memory components.

Overall, these findings suggest that cognitive linguistic translation, word-form coding, phonological loop, orthographic loop, supervisory attention, and executive functions all contribute uniquely to reading and writing achievement in children with specific learning disabilities. This highlights the usefulness of considering specific components of working memory and cognitive-linguistic translation when making learning disability diagnoses. Additionally, assessing these cognitive constructs in addition to academic achievement may also assist in individualizing instructional plans to improve academic achievement in children with specific learning disabilities.

Niedo, J., Abbott, R. D., & Berninger, V. W. (2014). Predicting levels of reading and writing achievement in typically developing, English-speaking 2nd and 5th graders. Learning and individual differences, 32, 54-68.

Blogger: Alex Cross is a M.Cl.Sc. and Ph.D. Candidate in Speech-Language Pathology, supervised by Dr. Lisa Archibald and Dr. Marc Joanisse.

Thursday, October 11, 2018

Newly-acquired words are more phonologically robust in verbal short-term memory when they have associated semantic representations

Savill, N., Ellis, A. W., & Jefferies, E. (2017). Newly-acquired words are more phonologically robust in verbal short-term memory when they have associated semantic representations. Neuropsychologia, 98, 85–97. https://doi.org/10.1016/j.neuropsychologia.2016.03.006.

It is well established that short-term or working memory codes phonological (or speech sounds of a word) information, while long-term memory holds semantic (meaning-based) information. Only recently has there been interest in looking at the effects of storing semantic information in short-term memory. A key question then is whether the learning of new phonological forms can benefit from semantic support.

In this study, participants learned new words that were trained with or without a semantic association. Words that had a semantic association were paired with an object and participants learned facts about that object, while words without semantic support were paired with a blurred image, without a central meaning. Learning was assessed immediately by a series of tests: participants were asked to recall any words they remembered (free recall); recall the words in the order they were presented (serial recall); and label the objects presented. On Day 2, participants were tested again using these tasks and were also asked to decide if the image matched the spoken label.

Overall the results suggest that word learning can benefit from being supported by meaning cues. Semantic effects also occurred immediately. Words paired with semantic cues had a slight advantage, with more phonemes recalled correctly compared to familiar words (i.e., words trained without semantic support) and new words; otherwise, performance for semantically-trained words and familiar words were comparable across all other tasks. Surprisingly, participants were poor at freely recalling items and naming pictures even though they successfully learned to link the word with the object and learned the semantic features about that object at the end of training. This suggests that word form and meaning might be encoded into long-term memory at least somewhat separately. It would follow that future work needs to consider when the link between word and meaning is being learned successfully and established in memory.

Blogger: Theresa is a MClSc/PhD Candidate, supervised by Dr. Lisa Archibald. Theresa’s work examines the learning of phonological (speech sound) and semantic (meaning) aspects of words.

Tuesday, July 10, 2018

A processing approach to the working memory/long-term memory distinction: Evidence from the levels-of-processing span task


Rose, N. S. & Craik, F. I. M. (2012). A processing approach to the working memory/long-term memory distinction: Evidence from the levels-of-processing span task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 1019-1029.

This paper examined whether long-term memory (LTM) can have effects on working memory (WM). LTM is a system for permanent knowledge, while WM is described as the ability to attend to relevant information while completing a task. Many models have been proposed to clarify the division between WM and LTM (e.g., multicomponent model, Baddeley, 1986; embedded models, Cowan, 1999). 
Perhaps one way to clarify the influence of LTM on WM is to examine how phenomena that have been known to impact LTM, also effect WM. For example, one hallmark finding related to LTM is that items are recalled better when they have been more deeply processed. Shallow processing might include repeating an item (phonological processing) whereas deep processing would involve making a connection with the meaning of a word (semantic processing). The present study investigated the influences of these Levels of Processing (LOP) on WM performance. In two studies, participants were first presented with questions cueing either a phonological judgment, “Does the following word RHYME with X?”, or a semantic judgement, “Is the following word a member of the CATEGORY X?" Participants were then shown a to-be-remembered word, about which they answered the question. After 4 to 8 items, participants had to recall all the to-be-remembered words, which was either a surprise (Exp. 2) or not (Exp. 1). This WM measure was compared for items to which rhyme or category judgments were made, which was considered to reflect either intermediate or deep processing, respectively. LTM was also measured in Exp. 1 by asking participants to choose the to-be-remembered words after a 10-min delay period. 
Not surprisingly, LTM benefited from LOP conditions, with better recognition for words processed semantically than phonologically. LOP effects in WM were mixed, however. A WM advantage was observed only for the immediate recall of 8-item lists in Exp. 2. Given that the test was a surprise in Exp. 2, participants might not have actively maintained the words by rehearsing them. As a result, those having been processed more deeply at initial encoding could have been recalled from LTM. 
These results suggest WM and LTM can be supported by the depth of processing of items in similar and different ways depending on encoding, maintenance and retrieval processes. Both phonological and semantic processing make contributions to WM and LTM. The findings suggest that encouraging deeper processing of a word at encoding will facilitate retention in the long term.  

Baddeley, A. D. (1986). Working memory. New York, NY: Clarendon Press/Oxford University Press.
Cowan, N. (1999). An embedded-processes model of working memory. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 62–101). New York, NY: Cambridge University Press.

Blogger: Theresa is a MClSc/PhD Candidate, supervised by Dr. Lisa Archibald. Theresa’s work examines the learning of phonological (speech sound) and semantic (meaning) aspects of words.

Friday, June 22, 2018

Implementation Research: Embracing Practitioners' Views

Feuerstein, J. L., Olswang, L. B., Greenslade, K. J., Dowden, P., Pinder, G. L., & Madden, J. (2018). Implementation research: Embracing practitioners' views. Journal of Speech, Language, and Hearing Research, 61(3), 645-657.

Implementation research is an active approach that bridges the gap between research and clinical practice. A core component of implementation research is the partnerships created between clinicians and researchers. These partnerships are established to help support the creation and uptake of new or changing clinical practices. Clinicians have insight into what is sustainable in clinical practice as well as other client and family specific preferences. Whereas researchers have knowledge about the specifics of the assessment and therapy protocols, and dosage requirements. Feuerstein et al. (2018) adopted an implementation research approach to gather clinicians’ opinions on a triadic gaze intervention (shifting eye gaze between a desired object and a parent) used to show communicative intent for children with moderate to severe motor delays.


Clinicians (occupational therapists, physiotherapists, and speech-language pathologists) were trained on the assessment and therapy protocols for a Triadic Gaze Intervention (TGI). Researchers were interested in (1) the clinicians’ knowledge and beliefs about early intervention, (2) the acceptability: how closely the clinicians’ view of early intervention aligned with the TGI and feasibility: facilitators and barriers to implementing the TGI protocols in practice, and (3) the feasibility of the clinician training for the TGI.  To answer these questions, two focus groups were conducted before and after the clinicians completed training and implemented the protocol with one client. Both focus groups were recorded and transcribed. Common emerging themes were coded to answer the questions posed by the researchers.


The clinicians reported that the TGI closely aligned with their views of early intervention. The TGI assessment, therapy, and training protocols had high acceptability and feasibility amongst the clinicians. As a result of the partnerships between clinicians and researchers, the researchers were able to gain insight into how the therapy and training should be adapted to better serve clinicians and families. More feedback throughout clinician training and a caregiver coaching model were two suggestions voiced by clinicians. Ultimately, this research demonstrates the importance of clinician-researcher partnerships to improve the integration of research into clinical practice.


Blogger: Meghan Vollebregt is a student in the combined SLP MSc/PhD program working under the supervision of Lisa Archibald.

Monday, May 14, 2018

An Integrated Brain-Behaviour Model for Working Memory



Moser, D.A., Doucet, G.E., Ing, A., Schumann, G., Bilder, R.M., Frangou, S. (2017). An integrated brain-behaviour model for working memory. Molecular Psychiatry (00), 1-7.

This paper examines function of the brain’s working memory (WM) network and how it relates to behavioural and health factors. Working memory refers to the ability to hold task-relevant information in mind. Previous studies have shown that WM depends on activity coordinated across multiple regions of the brain, including the dorsolateral prefrontal cortex, the parietal cortex, and the dorsal anterior cingulate cortex. Function of this WM network can be characterized using functional magnetic resonance imaging (fMRI), an imaging technique that measures brain activity by detecting changes associated with blood flow. Three fMRI methods were examined in this study: (1) Regional activation, which involves looking at functional activation in specific areas of the brain during a task. (2) Functional connectivity, which examines correlations in activity between different brain regions to infer how these areas are functionally connected. And (3) Effective connectivity, which studies systematic changes in activity over time to assess causal interactions between brain regions. Using these, the aim of the study was to examine the relationship between function of the brain’s WM network and behavioural and health factors.

Participants were 828 healthy adults, between 22 and 37 years old. They underwent an fMRI scan while performing a 2-back WM task, in which they were asked to indicate whether a visual stimulus matched the stimulus from two trials before. They also completed a number of measures of sensorimotor processing, cognition, mental health, personality, physical health, and lifestyle factors.

Using a statistical technique called sparse canonical correlations to examine relationships between the neuroimaging and behavioural-health datasets, results indicated a significant association between WM function and all behavioural variables. Positive correlations were observed for cognitive and physical attributes, and negative correlations observed for suboptimal health indicators and negative lifestyle choices. Results across the fMRI measures underscored a relationship between working memory and non-affective cognition for both activation of the regions within the network and connections between the network. Correlations with physical health variables were observed for other areas of the brain, suggesting that this relationship was not specific to the WM network.

Overall, these findings suggest that function of the WM network is optimal in individuals with better cognitive abilities and physical well-being, while functional connectivity across the whole brain is reduced in individuals with suboptimal health and substance abuse. This study highlights the usefulness of measuring connectivity across the brain when studying cognitive processes, rather than examining brain areas in isolation. Applied to clinical practice, this highlights the importance of making connections. Drawing links between information and integrating multiple modalities into therapy sessions may help to engage more brain areas and strengthen connections between these brain areas.

Blogger: Alex Cross is an M.Cl.Sc. and Ph.D. Candidate in Speech-Language Pathology, supervised by Dr. Lisa Archibald and Dr. Marc Joanisse.