Using Apps for Speech Therapy

It seems like only a few days ago I promised to write a blog post on the best uses of apps for speech therapy, when I wrote about the Werfel study in my last blogpost. But it turns out that I made that promise 3 months ago! Time flies when you are School Director it turns out. But also, my thinking about why you might want to substitute an app for picture cards reminded me of a particularly traumatic event in my past and maybe I just didn’t want to revisit that memory. But here goes…when I was sent out on my first summer practicum as an undergraduate student sometime in the nineteen-seventies I was assigned to a health unit in rural Alberta. The placement involved driving a great big Ford around to schools on country roads which was scary enough because I had a driver’s licence, but I had never really driven on account of not owning a car. Anyway, on the very first day my supervisor asked me to carry all our materials out to the car so she piled my arms up with stuff, many files filled with papers, some board games, those plastic boxes full of articulation cards, and on top of that…her lunch! Of course, I dropped the load in the parking lot. You can imagine the scene — I am not going to describe the process of picking it all back up and trying to reorder everything before getting it in the back seat. To make it all worse, she then hands me the keys and tells me to drive because she is going to eat her lunch on the way. Her lunch included a can of grape pop. Now you can imagine how my glasses became painted with purple goop. All I can says is that it is lucky I did not drive the car off the road.

This story is actually relevant to the topic at hand because I want to talk about iPad apps relative to all the things I was carrying in my hands, excluding the lunch. Recall that Werfel implemented a therapy program in which the children named pictures on the screen and then swiped them off, one after the other, for 25 sessions over 8 weeks. Is this how we want to use apps? Why would we use apps? What are the advantages of apps over the boxes of pictures cards? Let’s go through the advantages one at a time.

  1. Storage

The first obvious advantage is that all the information and functionality carried in the files, the boxes of picture cards and even the board games can be stored on an iPad — a relatively small object that would have fit in the lunch bag or my purse. Not only that, the information can be password protected so it is an efficient and relatively secure way of carrying things around. At the same time the screen is large enough for two people to view and small hands to manipulate. I read that SLPs use a lot of apps built for phones because their employers do not provide them with iPads but everyone has their own iPhone. That is a real shame because the functionality of an iPad or other tablet is hard to beat.

  1. Multimedia

The second advantage of a digital app is the possibility of presenting information to children with multimedia correlation across different sensory modalities. Apps can present therapy stimuli with an integration of colourful and realistic visual representations, integrated text, sound effects and movement. Susan Neuman’s theory of synergy predicts that children learn and store more robust mental representations when they experience new information this way. Some experimental support for this idea was presented by Strouse & Ganea who randomly assigned 102 toddler-mother pairs to a print-book or ebook shared reading condition. The results were striking:

“Toddlers who were read the electronic books paid more attention, made themselves more available for reading, displayed more positive affect, participated in more page turns, and produced more content-related comments during reading than those who were read the print versions of the books. Toddlers also correctly identified a novel animal labeled in the book more often when they had read the electronic than the traditional print books.”

In this study the animation provided by the ebooks was very simple: when the toddlers patted the page, the sound associated with the illustrated animal was presented. Therefore, we have multimedia stimulation and an interactive component contributing to engagement and learning.

  1. Interactive Features

The variety of interactive features that are built into apps are boundless. In ebooks “hotspots” within the text or illustrations launch a variety of effects that may advance the story and support learning. Alternatively these animations, sound effects and games that occur when the hotspots are activated may be entertaining while not relevant to the story at all. These same kind of features can be used to create learning activities in the context of educational games meant to teach letter sounds or vocabulary or reading or a wide range of other skills. Many games are simply digital versions of conventional board games. Other games are meant to be fun and creative, involving free style drawing, opportunities to create characters and settings and stories in an open-ended fashion. Apps that encourage creativity are recommended for their “minds-on” properties. Hirsh-Pasek et al presented a framework for evaluating and choosing apps that rests on four pillars of learning: (1) the app encourages active learning; (2) in which the child is deeply engaged by the learning task; (3) the learning experience is meaningful in that it promotes connections between new knowledge and existing knowledge; and (4) the learning activity permits high quality social interaction or social contingency. These authors also review the science of learning and conclude that when the app is explicitly educational the learning program should be structured to provided “scaffolded exploration toward a learning goal.” Therefore, rote learning games in which the child, for example, simply names pictures and receives a tangible reward such as points in a token-economy game would not meet these criteria. A completely open-ended game with no learning goal would also not meet these criterial.

  1. Personalization

Perhaps the most exciting opportunities offered by tablets and the associated apps are the possibilities for personalization. It is possible for children to create their own stimuli and stories using the camera, drawing, and writing tools. In this way all the practice materials for speech and language therapy can be especially meaningful and relevant to the child’s daily life and special interests.

Using Apps in Speech Therapy

The first advantage to using apps in speech therapy is that it is possible to “think outside the articulation card box” and use other tools to practice speech accuracy in authentic communicative contexts. Let us imagine that you are working of velar stops with a child who typically fronts these consonants. You want an opportunity to product the sounds in relatively complex words while providing meaningful feedback using focused stimulation that is adapted for the speech therapy context as described by Rvachew & Brosseau-Lapré (2012). There are some electronic books that lend themselves to conversation that useful for this purpose. Consider the Nosy Crow book “Don’t Wake Up Tiger!” First there are several opportunities to produce velar sounds in conversation: tiger (contrasted with turtle), frog, cake, candle, pelican, fox). There is an active learning component in that the child must perform specific actions to help the different animals get around the tiger without waking him up in order to set up their surprise birthday party. There are matching games and five “spot the difference” games, the last one involving the birthday party scene, providing the opportunity for distancing prompts. The idea here is that articulation drill is not the best way to improve speech accuracy for the majority of children with speech delay or disorders in any case. You will want to choose different stories or games for older children but definitely choose apps that permit authentic conversation and minds-on learning.

It is also possible to create your own games for speech therapy drill very simply using presentation tools along with photos, clip art, or drawing tools. If you were practicing words that contain siblilants for example, the child could bring a photo of his house. Pasted into a series of slides, over top of cartoon characters and animated to disappear upon clicking or swiping, you have a very simple game. In this case, the child asks the question “Whose house?” and after swiping the house, a simple animation reveals the “It’s mouse’s house (sheep’s/zebra’s/seal’s etc.).” Many common software tools permit simple animations that are useful, turning a simple swipe into a game that connects meaning to the drill practice.

Of course, there are many commercial apps for drill therapy or minimal pairs games. I will not make the mistake of endorsing or criticizing any particular product. However, you will want to look for common problems when you download free games or purchase more sophisticated therapy tools. One common issue is putting text on the minimal pair cards so that the children are using letter cues rather than listening to the sound of speech and referring to their own underlying representations for words when playing the game that is involved. Another issue is poor choices of words from the point of view of phonological theory (e.g., “ball” and “bottle” are not both /l/-coda words). The old articulation card boxes had the same problem but it was often easier to shuffle through and exclude the words that did not fit the pattern you were working on. The commercial apps may or may not be that flexible.

In any case, I am sure that most of you are more familiar with these apps than I am and have lots of creative ideas for using them. The main point I wanted to make is that we should not let the tail wag the dog. It is really important to choose the most creative minds-on apps and not let the software coax us way back to the “drill and kill” days of the sixties. We have known for some time now that phonological therapy is all about meaning. The fun part of digital tools is the opportunity that multimedia and interactivity offers for helping children make connections between new learning and their prior experience.

How to score iPad SAILS

As the evidence accrues for the effectiveness of SAILS as a tool for assessing and treating children’s (in)ability to perceive certain phoneme contrasts (see blog post on the evidence here), the popularity of the new iPad SAILS app is growing. Now I am getting questions about how to score the new SAILS app on the iPad so I provide a brief tutorial here. The norms are not built into the app since most of the modules are not normed. However, four of the modules are associated with normative data and can be used to give a sense of whether children’s performance is within the expected range according to age/grade level. Those normative data have been published in our text “Developmental Phonological Disorders: Foundations of Clinical Practice” (derived from the sample described in Rvachew, 2007) but I reproduce the table here and show how to use it.

When you administer the modules lake, cat, rat and Sue you will be provided with an overall Level score for all the Levels in each module as well as item by item scores on the Results page. As an example, I show the results page below after administering the  rat module.

SAILS results screenshot rat

The screen shot shows the item-by-item performance on the right hand side for Level 2 of the rat module. On the left hand side we can see that the total score for Level 2 was 7/10 correct responses and the total score for Level 1 was 9/10 correct responses (we ignore responding to the Practice Level). To determine if the child’s perception of “r” is within normal limits, average performance across Levels 1 and 2: [(9+7)/20]*100 = 80% correct responses. This score can be compared to the normative data provided in Table 5-7 of the second edition of the DPD text, as reproduced below:

SAILS Norms RBL 2018

Specifically a z-score should be calculated: (80-85.70)/12.61 = -.45. In other words, if the child is in first grade, the z score is calculated by taking the obtained score of 80% minus the expected score of 85.70% and dividing the result by the standard deviation of 12.61 which gives a z score that is less than one standard deviation below the mean. Therefore, we are not concerned about this child’s perceptual abilities for the “r” sound. When calculating these scores, observe that some modules have one test level, some have two and some have three. Therefore the average score is sometimes based on 10 total responses, sometimes on 20 total responses as shown here, and sometimes on 30 total responses.

The child’s total score across the four modules lake, cat, rat and Sue can be averaged (ignoring all the practice levels) and compared against the means in the row labeled “all four”. Typically you want to know about the child’s performance on a particular phoneme however because generally children’s perceptual difficulties are linked to those phonemes that they misarticulate.

Normative data has not been obtained for any of the other modules. Typically however, a score of 7/10 or less than 7/10 is not a good score – a score this low suggests guessing or not much better than guessing given that this is a two alternative forced choice task.

Previously we have found that children’s performance on this test is useful for treatment planning in that children with these speech perception problems will achieve speech accuracy faster when the underlying speech perception problem is treated. Furthermore, poor overall speech perception performance  in children with speech delay is associated with slower development of phonological awareness and early reading skills.

I hope that you and your clients enjoy the SAILS task which can be found on the App Store, with new modules uploaded from time to time: https://itunes.apple.com/ca/app/sails/id1207583276?mt=8

 

How effective is phonology treatment?

Previously I asked whether it made sense to calculate effect sizes for phonology therapy at the within subject level. In other words, from the clinical point of view, do we really want to know whether the child’s rate of change is bigger during treatment than it was when the child was not being treated? Or, do we want to know if the child’s rate of change is bigger than the average amount of change observed among groups of children who get treated? If children who get treated typically change quite a bit and your client is not changing much at all, that might indicate a course correction (and note please, not a treatment rest!). From this perspective, group level effect sizes might be useful so I am providing raw and standardized effect sizes here from three of my past studies with a discussion to follow.

Rvachew, S., & Nowak, M. (2001). The effect of target selection strategy on sound production learning. Journal of Speech, Language, and Hearing Research, 44, 610-623.

The first data set involves 48 four-year-old children who scored at the second percentile, on average, on the GFTA (and 61 percent consonants correct in conversation). They were randomly assigned to receive treatment for relatively early developing stimulable sound targets (ME group, n=24) or late developing unstimulable sound targets (LL group, n=24). Each received treatment for four sounds over 2 six-week blocks, during 12 30 to 40 minute treatment sessions. The treatment approach employed traditional articulation therapy procedures. The children did not receive homework or additional speech and language interventions during this 12 week period. Outcome measures included single word naming probes covering all consonants in 3 word positions and percent consonants correct (PCC) in conversation, with 12 to 14 weeks intervening between the pre- and the post-test assessments. The table below shows two kinds of effect sizes for the ME group and the LL group: the raw effect size (raw ES) with the associated confidence interval (CI) which indicates the mean pre- to post-change in percent consonants corrects on probes and in conversation; next is the standardized mean difference, Cohen’s d(z); finally, I show the number and percentage of children who did not change (0 and negative change scores). These effect sizes are shown for three outcome measures: single word naming probe scores for unstimulable phonemes, probe scores for stimulable phonemes, and percent consonants correct (PCC) obtained from conversations recorded while the child looked at a wordless picture book with the assessor.Effect size blog figure 2.

Some initial conclusions can be drawn from this table. The effect sizes for change in probe scores are all large. However, the group that received treatment for stimulable sounds showed greater improvement for both treated stimulable sounds and untreated unstimulable sounds compared to the group that received treatment for unstimulable sounds. There was almost no change in PCC derived from the conversational samples overall. I can report that 10 children in the ME group and 6 children in the LL group achieved improvements of greater than 5 PCC points, judged to be a “minimally important change”  by Thomas-Stonell et al. (2013). Half the children achieved no change at all however in PCC (conversation).

Rvachew, S., Nowak, M., & Cloutier, G. (2004). Effect of phonemic perception training on the speech production and phonological awareness skills of children with expressive phonological delay. American Journal of Speech-Language Pathology, 13, 250-263.

The second data set involves 34 four-year-old children who scored at the second percentile, on average, on the GFTA (and approximately 60 percent consonants correct in conversation). All of the children received 16 hour-long speech therapy sessions, once-weekly. The treatment that they received was entirely determined by their SLP with regard to target selection and approach to intervention. Ten SLPs provided the interventions, 3 using the Hodson cycles approach, 1 a sensory motor approach and the remainder using a traditional articulation therapy approach. The RCT element of this study is that the children were randomly assigned to an extra treatment procedure that occurred during the final 15 minutes of each session, concealed from their SLP. Children in the control group (n=17) listened to ebooks and answered questions. Children randomly assigned to the PA group (n=17) played a computer game that targeted phonemic perception and phonological awareness covering 8 phonemes in word initial and then word final position. Although the intervention lasted 4 months, the interval between pre-treatment and post-treatment assessments was 6 months long. The table below shows two kinds of effect sizes for the ME group and the LL group: the raw effect size (raw ES) with the associated confidence interval (CI) indicates the mean pre- to post-change in percent consonants correct; next is the standardized mean difference, Cohen’s d(z); finally, I show the number and percentage of children who did not change (0 and negative change scores). These effect sizes are shown for two outcome measures: percent consonants correct (PCC) obtained from conversations recorded while the child looked at a wordless picture book with the assessor; and PCC-difficult, derived from the same conversations but restricted to phonemes that were produced with less than 60% accuracy at intake-in other words, phonemes that were potential treatment targets, specifically /ŋ,k,ɡ,v,ʃ,ʧ,ʤ,θ,ð,s,z,l,ɹ/.

Effect size blog figure 3

The sobering finding here is that the control group effect size for potential treatment targets is the smallest, with half the group making no change and the other half making a small change. The effect size for PCC (all) in the control group is more satisfying in that it is better than the minimally important change (i.e., 8% > 5%); 13 children in this group achieved a change of more than 5 points and only 3 made no change at all. The effect sizes are large in the group that received the Speech Perception/PA intervention in addition to their regular SLP program with good results for PCC (all) and PCC-difficult. This table shows that the SLP’s choice of treatment procedures makes a difference to speech accuracy outcomes.

Rvachew, S., & Brosseau-Lapré, F. (2015). A randomized trial of twelve week interventions for the treatment of developmental phonological disorder in francophone children. American Journal of Speech-Language Pathology, 24, 637-658. doi:10.1044/2015_AJSLP-14-0056

The third data set involves data from 64 French-speaking four-year-olds who were randomly assigned to receive either an output oriented intervention (n = 30) or an input-oriented intervention (n = 34) for remediation of their speech sound disorder. Another 10 children who were not treated also provide effect size data here. The children obtained PCC scores of approximately 70% on the Test Francophone de Phonologie, indicating severe speech sound disorder (consonant accuracy is typically higher in French-speaking children, compared to English). The children received other interventions as well as described in the research report (home programs and group phonological awareness therapy) with the complete treatment program lasting 12 weeks. The table below shows two kinds of effect sizes for the ME group and the LL group: the raw effect size (raw ES) with the associated confidence interval (CI) indicates the mean pre- to post-change in percent consonants correct; next is the standardized mean difference, Cohen’s d(z); finally, I show the number and percentage of children who did not change (0 and negative change scores). These effect sizes are shown for two outcome measures: percent consonants correct with glides excluded (PCC), obtained from the Test Francophone de Phonologie, a single word naming test; PCC-difficult, derived from the same test but restricted to phonemes that were produced with less than 60% accuracy at intake-specifically /ʃ,ʒ,l,ʁ/. An outcome measure restricted to phonemes that were absent from the inventory at intake is not possible for this group because French-speaking children with speech sound disorders have good phonetic repertoires for the most part as their speech errors tend to involve syllable structure (see Brosseau-Lapré and Rvachew, 2014).

Effectsize blog figure 4

There are two satisfying findings here: first, when we do not treat children with a speech sound disorder, they do not change, and when we do treat them, they do! Second, when children receive an appropriate suite of treatment elements, large changes in PCC can be observed even over an observation interval as short as 12 weeks.

Overall Conclusions

  1. In the introductory blog to this series, I pointed out that Thomas-Stonell and her colleagues had identified a PCC change of 5 points as a “minimally important change”. The data presented here suggests that this goal can be met for most children over a 3 to 6 months period when children are receiving an appropriate intervention. The only case where this minimum standard was not met on average was in Rvachew & Nowak (2001), a study in which a strictly traditional articulation therapy approach was implemented at low intensity with no homework component.
  2. The measure that we are calling PCC-difficult might be more sensitive and more ecologically valid for 3 and 6 month intervals. This is percent consonants correct, restricted to potential treatment targets, so those consonants that are produced with less than 60% accuracy at intake. These turn out to be mid- to late-developing frequently misarticulated phonemes, therefore /ŋ,k,ɡ,v,ʃ,ʧ,ʤ,θ,ð,s,z,l,ɹ/ in English and /ʃ,ʒ,l,ʁ/ in French for these samples of 4-year-old children with severe and moderate-to-severe primary speech sound disorders. My impression is that when providing an appropriate intervention an SLP should expect at least a 10% change in these phonemes whether assessed with a broad based single word naming probe or in conversation-in fact a 15% change is closer to the average. This does not mean that you should treat the most difficult sounds first! Look carefully at the effect size data from Rvachew and Nowak (2001): when we treated stimulable phonemes we observed a 15% improvement in difficult unstimulable sounds. You can always treat a variety of phonemes from different levels of the phonological hierarchy as described in a previous blog.
  3. Approximately 10% of 4-year-old children with severe and moderate-to-severe primary speech sound disorders do not improve at all over a 3 to 6 month period, given adequate speech therapy. If a child is not improving, the SLP and the parent should be aware that this is a rare event that requires special attention.
  4. In a previous blog I cited some research evidence for the conclusion that patients treated as part of research trials achieve better outcomes than patients treated in a usual care situation. There is some evidence for that in these data. The group in Rvachew, Nowak and Cloutier that received usual care obtained a lower effect size (d=0.45) in comparison to the group that received an extra experimental intervention (d=1.31). In practical terms this difference meant that the group that received the experimental intervention made four times more improvement in the production of difficult sounds than the control group that received usual care.
  5. The variation in effect sizes that is shown in these data indicate that SLP decisions about treatment procedures and service delivery options have implications for success in therapy. What are the characteristics of the interventions that led to relatively large changes in PCC or relatively large standardized effect sizes? (i) Comprehensiveness, that is the inclusion of intervention procedures that target more than one level of representation, e.g., procedures to improve articulation accuracy and speech perception skills and/or phonological awareness; and (ii) parent involvement, specifically the inclusion of a well-structured and supported home program.

If you see other messages in these data, or have observations from your own practice or research, please write to me in the comments.

 

 

How to choose phonology goals?

I find out via Twitter (don’t you love twitter!) that “teach complex sounds first” is making the rounds again (still!) and I am prompted to respond. Besides the fact that I have disproven the theoretical underpinnings of this idea, it bothers me that so many of the assumptions wrapped up in the assertion are unhelpful to a successful intervention. Specifically, we should not be treating “sounds”, there is no agreed upon and universal ordering of targets from simple to complex, and there is no reason to teach the potential targets one at a time in some particular order anyway. So what should we do? I will describe a useful procedure here with an example.

There is this curious rumour that I promote a “traditional developmental” approach to target selection that I must lay to rest. In fact, I have made it clear that I promote a dynamic systems approach. An important concept is the notion of nonlinearity: if you induce gradual linear changes in several potential targets at once, a complex interaction will result causing a nonlinear change across the system known as a phase shift. How do you choose the targets to work on at once? Francoise and I show how to use a “quick multilinear analysis” to identify potential targets  at all levels of the phonological hierarchy, in other words phrases, trochaic or iambic feet, syllables, onsets, rimes or codas, clusters, features or individual phonemes. Many case studies and demonstrations are laid out in our book that will shortly appear in a beautiful second edition. Then we show how to select three targets for simultaneous treatment using Grunwell’s scheme designed to facilitate progressive change in the child’s phonological system. I will demonstrate both parts of this process here, using a very brief sample from a case study that is described in our book. The child’s speech is delayed for her age of two years which can be established by comparing the word shape and phonetic repertoire to expectations established by Carol Stoel-Gammon.

case-study-6-3-sample-for-blog

Potential treatment targets can be identified by considering strengths and weaknesses at the prosodic and segmental tiers of the phonological hierarchy (full instructions for this quick multilinear analysis are contained in our book). The table below describes units that are present and absent. Note that since her language system is early developing, her phonology is probably word-based rather than phoneme based; therefore ‘distinction’ refers to the presence of a phonetic distinction rather than a phonemic contrast.

case-study-6-3-quick-multilinear-analysis

Now that we have a sense of potential targets from across the whole system, how do we select targets using Grunwell’s scheme? We want to ensure that we address word shape and segmental goals. We also want to choose one goal to stabilize a variable structure in the system, another to extend something that is established to a new context, and a third to expand the system to including something new. Here are my choices (others are possible):

case-study-6-3-grunwell-goals

There is a good chance that fricatives and codas will emerge spontaneously with this plan because we will have laid down the foundation for these structures. If they don’t it should not be hard to achieve them during the next therapy block. The idea that you can only induce large change in the system by teaching the most complex targets first is clearly not true as I have explained previously – in fact, complex sounds emerge more easily when the foundation is in place. Furthermore, Schwartz and Leonard (1982) also recommended in their study on selection effects in early phonological development that it was best to teach IN words to children with small vocabulary sizes – in other words expand the vocabulary size gradually by using word shapes and phonemes that are in the inventory, but combined in new ways.

It would be possible to use the stabilize-extend-expand scheme and choose different, more complex goals. For example, we could consider the nonreduplicated CVCV structure (cubby, bunny, bootie) to be the stabilize goal. Then we could introduce word final labial stops as the extend goal, generalizing these phones from the onset where they are well established to a new word position (up, tub, nap). Finally, we could introduce a word initial fricative as the expand goal (see, sock, soup). This plan with more complex targets might work but you are risking slower progress, given the empirical findings reported in Rvachew & Nowak (2001) and in Schwartz & Leonard (1982). Furthermore, you would be failing to recognize a major constraint on the structure of her syllables (the limitation to only 2 segments, VV or CV with CVV and CVC currently proscribed). If you focus only on introducing “complex sounds” without attending to this major issue at the prosodic levels of her phonological system, you will be in for a rough ride.

I attach here another example, this one a demonstration from the second edition of our book, chapter-8-demonstration-8-2, to appear in December 2016. Francoise and I have taken a great effort to show students how to implement an evidence based approach to therapy. I invite readers to take a peak!

Reading List

Rvachew, S., & Brosseau-Lapré, F. (2018). Developmental Phonological Disorders: Foundations of Clinical Practice (Second Edition). San Diego, CA: Plural Publishing. (Ready for order in December 2016)

Grunwell, P. (1992). Processes of phonological change in developmental speech disorders. Clinical Linguistics & Phonetics, 6, 101-122.

Stoel-Gammon, C. (1987). Phonological skills of 2-year-olds. Language, Speech & Hearing Services in Schools, 18, 323-329.

Rvachew, S., & Bernhardt, B. (2010). Clinical implications of the dynamic systems approach to phonological development. American Journal of Speech-Language Pathology, 19, 34-50.

Rvachew, S. & Nowak, M. (2001). The effect of target selection strategy on sound production learning. Journal of Speech, Language, and Hearing Research, 44, 610-623.

Schwartz, R., & Leonard, L. (1982). Do children pick and choose? An examination of selection and avoidance in early lexical acquisition. Journal of Child Language, 9, 319-336.