What is a control group?

I have a feeling that my blog might become less popular in the next little while because you may notice an emerging theme on research design and away from speech therapy procedures specifically! But it is important to know how to identify evidence based procedures and to do that requires knowledge of research design and it has come to my attention, as part of the process of publishing two randomized control trials (RCTs) this past year, that there are a lot of misperceptions about what an RCT is in the SLP and education communities, among both clinicians and researchers. Therefore, I am happy to draw your attention to this terrific blog by Edzard Ernst, and in particular to an especially useful post “How to differentiate good from bad research”. The writer points out that a proper treatment of this topic “must inevitably have the size of a book” because each of the indicators that he provides “is far too short to make real sense.” So I have taken it upon myself in this blog to expand upon one of his indicators of good research – one that I know causes some confusion, specifically:

  • Use of a placebo in the control group where possible.

Recently the reviewers (and editor) of one of my studies was convinced that my design was not an RCT because the children in both groups received an intervention. In the absence of a “no-treatment control” they said, the study could not be an RCT! I was mystified about the source of this strange idea until I read Ernst’s blog and realized that many people, recalling their research courses from university, must be mistaking “placebo control” for “no-treatment control.” However, a placebo control condition is not at all like the absence of treatment. Consider the classic example of a placebo control: in a drug trial, the patients randomized to the treatment arm will visit the nurse who hands him or her a white paper cup holding 2 pink pills containing active ingredient X and some other ingredients that do not impact the patient’s disease, i.e., inactive ingredients; the patients randomized to the control arm will also visit the nurse who hands him or her a white paper cup holding 2 pink pills containing only the inactive ingredients. In other words, the experiment is designed so that all patients are “treated” exactly the same except that only patients randomized to treatment receive (unknowingly) the active ingredient. Therefore, all changes in patient behavior that are due to those aspects of the treatment that are not the active treatment (visiting the nice nurse, expecting the pills to make a difference etc.) are equalized across arms of the study. These are called the “common factors” or “nonspecific factors”.

In the case of a behavioral treatment it is important to equalize the common factors across all arms of the study. Therefore in my own studies I deliberately avoid “no treatment” controls. In my very first RCT (Rvachew, 1994) for example the treatment conditions in the two arms of the study were as follows;

  • Experimental: 10 minutes of listening to sheet vs Xsheet recordings and judging correct vs incorrect “sheet” items (active ingredient) in a computer game format followed by 20 minutes of traditional “sh” articulation therapy, provided by a person blind to the computer game target.
  • Control: 10 minutes of listening to Pete vs meat recordings and judging correct vs incorrect “Pete” items in a computer game format followed by 20 minutes of traditional “sh” articulation therapy, provided by a person blind to the computer game target.

It can be seen that the study was designed to ensure that all participants experienced exactly the same treatment except for the active ingredient that was reserved for children who were randomly assigned to the experimental treatment arm, specifically exposure to the experience of listening to and making perceptual judgments about a variety of correct and incorrect versions of words beginning with “sh” or distorted versions of “sh”-the sound that the children misarticulated. Subsequently I have conducted all my randomized control studies in a similar manner. But, as I said earlier, I run across readers who vociferously assert that the studies are not RCTs because an RCT requires a “no treatment” control. In fact, a “no treatment” control is a very poor control indeed as argued in this blog that explains why the frequently used “wait list control group” is inappropriate. For example, a recent trial on the treatment of tinnitus claimed that a wait list control had merit because “While this comparison condition does not control for all potential placebo effects (e.g., positive expectation, therapeutic contact, the desire to please therapists), the wait-list control does account for the natural passing of time and spontaneous remission.” In fact, it is impossible to control for common factors when using a wait list control and it is unlikely that patients are actually “just waiting” when you randomize them to the “wait list control” condition; therefore Hesser et al.’s defense of the wait list control is  optimistic although their effort to establish how much change you get in this condition is worthwhile.

We had experience with a “wait list” comparison condition in a recent trial (Rvachew & Brosseau-Lapré, 2015). Most of the children were randomly assigned to one of four different treatment conditions, matched on all factors except the specific active ingredients of interest. However, we also had a nonexperimental wait list comparison group* to estimate change for children outside of the trial. We found that parents were savvy about maximizing the treatment that their children could receive in any given year. Our trial lasted six weeks, the public health system entitled them to six weeks of treatment and their private insurance entitled them to six to 12 weeks of therapy depending on the plan. Parents would agree to enrolled their child in the trial with randomization to a treatment arm if their child was waiting for the public service, OR they would agree to be assessed in the “wait list” arm if their child was currently enrolled in the public service. They would use their private insurance when all other options had been exhausted. Therefore the children in the “wait list” arm were actually being treated. Interestingly, we found that the parents expected their children to obtain better results from the public service because it was provided by a “real” SLP rather than the student SLPs who provided our experimental treatments even though the public service was considerably less intense! (As an aside, we were not surprised to find that the reverse was true). Similarly, as I have mentioned in previous blogs, Yoder et al. (2005) found that the children in their “no treatment” control accessed more treatment from other sources than did the children in their treatment arm. And parents randomized to the “watchful waiting” arm of the Glogowska et al. (2000) trial sometimes dropped out because parents will do what they must to meet their child’s needs.

In closing, a randomized control trial is simply a study in which participants are randomly assigned to an experimental treatment and a control condition (even in a cross-over design, in which all participants experience all conditions, as in Rvachew et al., in press). The nature of the control should be determined after careful thought about the factors that you are attempting to control, which can be many – placebo, Hawthorne, fatigue, practice, history, maturation and so on. These will vary from trial to trial obviously. Placebo control does not mean “no treatment” but rather, a treatment that excludes everything except the “active ingredient” that is the subject of your trial. As an SLP, when you are reading about studies that test the efficacy of a treatment, you need to pay attention to what happens to the control group as well as the treatment group. The trick is to think in every case – what is the active ingredient that explains the effect seen in the treatment group? what else might account for the effects seen in the treatment arm of this study? If I implement this treatment in my own practice, how likely am I to get a better result compared to the treatment that my caseload is currently receiving?

* A colleague sent me a paper (Mercer et al., 2007) in which a large number of researchers advocating for the acceptance of a broader array of research designs in order to focus more attention on external validity and translational research, got together to discuss the merits of various designs. During the symposium it arose that there was disagreement about the use of the terms “control” and “comparison” group. I use the terms in accordance with a minority of their attendees, as follows: control group means that the participants were randomly assigned to a group that did not experience the “active ingredient” of the experimental treatment; comparison group means that the participants were not randomly assigned to the group that did not experience the experimental intervention, a group that may or may not have received a treatment. This definition was ultimately not used by the attendees, I don’t know why – somehow they decided on a different definition that didn’t make any sense at all, I invite you to consult p. 141 and see if you can figure it out!

References

Glogowska, M., Roulstone, S., Enderby, P., & Peters, T. (2000). Randomised controlled trial of community based speech and language therapy in preschool children. British Medical Journal, 321, 923-928.

Hesser, H., Weise, C., Rief, W., & Andersson, G. (2011). The effect of waiting: A meta-analysis of wait-list control groups in trials for tinnitus distress. Journal of Psychosomatic Research, 70(4), 378-384. doi:http://dx.doi.org/10.1016/j.jpsychores.2010.12.006

Mercer, S. L., DeVinney, B. J., Fine, L. J., Green, L. W., & Dougherty, D. (2007). Study Designs for Effectiveness and Translation Research: Identifying Trade-offs. American Journal of Preventive Medicine, 33(2), 139-154.e132. doi:http://dx.doi.org/10.1016/j.amepre.2007.04.005

Rvachew, S. (1994). Speech perception training can facilitate sound production learning. Journal of Speech and Hearing Research, 37, 347-357.

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

Rvachew, S., Rees, K., Carolan, E., & Nadig, A. (in press). Improving emergent literacy with school-based shared reading: Paper versus ebooks. International Journal of Child-Computer Interaction. doi:http://dx.doi.org/10.1016/j.ijcci.2017.01.002

Yoder, P. J., Camarata, S., & Gardner, E. (2005). Treatment effects on speech intelligibility and length of utterance in children with specific language and intelligibility impairments. Journal of Early Intervention, 28(1), 34-49.

Using effect sizes to choose a speech therapy approach

I am quite intrigued by the warning offered by Adrian Simpson in his paper “The misdirection of public policy: comparing and combining standardized effect sizes

The context for the paper is the tendency of public policy makers to rely on meta-analyses to make decisions such as, for example, should we improve teachers’ feedback skills or reduce class sizes as a means of raising student performance? Simpson shows that that meta-analyses (and meta-analyses of the meta-analyses!) are a poor tool for making these apples to oranges comparisons and cannot be relied upon as a source of information when making public policy decisions such as this. He identifies three specific issues with research design that invalidate the combining and comparing of effect sizes. I think that these are good issues to keep in mind when considering effect sizes as a clue to treatment efficacy and a source of information when choosing a speech or language therapy approach.

Recall that an effect size is a standardized mean difference, whereby the difference between means (i.e., the mean outcome of the treatment condition versus the mean outcome of the control condition) is expressed in standard deviation units. The issue is that the standard deviation units, which are supposed to reflect the variation in outcome scores between participants in the intervention trial, actually reflect many different aspects of the research design. Therefore if you compare the effect size of an intervention as obtained in one treatment trial with the effect size for another intervention as obtained in a different treatment trial, you cannot be sure that the difference is due to differences in the relative effectiveness of the two treatments. And yet, SLPs are asking themselves these kinds of questions every day: should I use a traditional articulation therapy approach or a phonological approach? Should I add nonspeech oral motor exercises to my traditional treatment protocol? Is it more efficient to focus on expressive language or receptive language goals? Should I use a parent training approach or direct therapy? And so on. Why is it unsafe to combine and compare effect sizes across studies to make these decisions?

The first issue that Simpson raises is that of comparison groups. Many, although not all, treatment trials compare an experimental intervention to either a ‘no treatment’ control group or a ‘usual care’ condition. The characteristics of the ‘no treatment’ and ‘usual care’ controls are inevitably poorly described if at all. And yet meta-analyses will combine effect sizes across many studies despite having a very poor sense of what the control condition is in the studies that are included in the final estimate of treatment effect. Control group and intervention descriptions can be so paltry that in some cases the experimental treatment of one study may be equivalent to the control condition of another study. The Law et al. (2003) review combined effect sizes for a number of RCTs evaluating phonological interventions. One intervention compared a treatment that was provided in 22 twice-weekly half hours sessions over a four month period to a wait list control (Almost & Rosenbaum, 1998). Another intervention involved monthly 45 minute sessions provided over 8 months, in comparison to a “watchful waiting” control in which many parents “dropped out” of the control condition (Glogowska et al. 2000). Inadequate information was provided about how much intervention the control group children accessed while they waited almost anything is possible relative to the experimental condition in the Glogowska trial. For example, Yoder et al. (2005) observed that their control group actually accessed more treatment than the kids in their experimental treatment group which maybe explains why they did not obtain a main effect of their intervention (or not, who knows?). The point is that it is hard to know whether a small effect size in comparison to a robust control is more or less impressive than a large effect size in comparison to no treatment at all. Certainly, the comparison is not fair.

The second issue raised concerns range restriction in the population of interest. I realize now that I failed to take this into account when I repeated (in Rvachew & Brosseau-Lapré, 2018) the conclusion that dialogic reading interventions are more effective for low-income children than children with developmental language impairments (Mol et al., 2008). Effect sizes are inflated when the intervention is provided to only a restricted part of the population, and the selection variables are associated with the study outcomes. However, the inflation is greatest for the children near the middle of the distribution and least for children at the tails of the distribution. This fact may explain why effect sizes for vocabulary size after dialogic reading intervention are highest for middle class children (.58, Whitehurst et al. 1988), in the middle for lower class but normally developing children (.33, Lonigan & Whitehurst, 1998), and lowest for children with language impairments (.13, Crain-Thoreson & Dale, 1999). There are other potential explanatory factors in these studies but this issue with restricted range is an important variable that is of obvious importance in treatment trials directed at children with speech and language impairments. The low effect size for dialogic reading obtained by Crain-Thoreson & Dale should not by itself discourage use of dialogic reading with this population.

Finally, measurement validity plays a huge role with longer more valid tests improving effect sizes in comparison to shorter less valid tests. This might be important when comparing the relative effectiveness of therapy for different types of goals. Law et al. (2003) concluded that phonology therapy appeared to be more effective than therapy for syntax goals for example. For some reason the outcome measures in these two groups of studies tend to be very different. Phonology outcomes are typically assessed with picture naming tasks that include 25 to 100 items, with the outcome often expressed as percent consonants correct and therefore at the consonant level there are many items contributing to the test score. Sometimes the phonology outcome measure is created specifically to probe the child’s progress on the specific target of the phonology intervention. In both cases the outcome measure is likely to be a sensitive measure of the outcomes of the intervention. Surprisingly, in Law et al., the outcome of the studies of syntax interventions were quite often omnibus measures of language functioning, such as the Preschool Language Scale, or worse the Reynell Developmental Language Scale, neither test containing many items targeted specifically at the domain of the experimental intervention. When comparing effect sizes across studies, it is crucial to be sure that the outcome measures have equal reliability and validity as measures of the outcomes of interest.

My conclusion is that it is important to not make a fetish of meta-analyses and effect sizes. These kinds of studies provide just one kind of information that should be taken into account when making treatment decisions. Their value is only as good as the underlying research—overall, effect sizes are most trustworthy when they come from the same study or a series of studies involving the exact same independent and dependent variables and the same study population. Given that this is a rare occurrence in speech and language research, there is no real substitute for a deep knowledge of an entire literature on any given subject. Narrative reviews from “experts” (a much maligned concept!) still have a role to play.

References

Almost, D., & Rosenbaum, P. (1998). Effectiveness of speech intervention for phonological disorders: a randomized controlled trial. Developmental Medicine and Child Neuroloogy, 40, 319-325.

Crain-Thoreson, C., & Dale, P. S. (1999). Enhancing linguistic performance: Parents and teachers as book reading partners for children with language delays. Topics in Early Childhool Special Education, 19, 28-39.

Glogowska, M., Roulstone, S., Enderby, P., & Peters, T. (2000). Randomised controlled trial of community based speech and language therapy in preschool children. British Medical Journal, 321, 923-928.

Law, J., Garrett, Z., & Nye, C. (2003). Speech and language therapy interventions for children with primary speech and language delay or disorder (Cochrane Review). Cochrane Database of Systematic Reviews, Issue 3. Art. No.: CD004110. doi:10.1002/14651858.CD004110.

Lonigan, C. J., & Whitehurst, G. J. (1998). Relative efficacy of a parent teacher involvement in a shared-reading intervention for preschool children from low-income backgrounds. Early Childhood Research Quarterly, 13(2), 263-290.

Mol, S. E., Bus, A. G., de Jong, M. T., & Smeeta, D. J. H. (2008). Added value of dialogic parent-child book readings: A meta-analysis. Early Education and Development, 19, 7-26.

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

Simpson, A. (2017). The misdirection of public policy: comparing and combining standardised effect sizes. Journal of Education Policy, 1-17. doi:10.1080/02680939.2017.1280183

Whitehurst, G. J., Falco, F., Lonigan, C. J., Fischel, J. E., DeBaryshe, B. D., Valdez-Menchaca, M. C., & Caulfield, M. (1988). Accelerating language development through picture book reading. Developmental Psychology, 24, 552-558.

Yoder, P. J., Camarata, S., & Gardner, E. (2005). Treatment effects on speech intelligibility and length of utterance in children with specific language and intelligibility impairments. Journal of Early Intervention, 28(1), 34-49.

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.

 

 

 

Using Phonetics to Teach Phonology

Francoise and I have been working on the second edition of our book for some time now and the book is finally in the production stage – counting down to a December 2016 release date. One of the decisions we have had to make is whether to keep all the figures that were in the first edition – we must pay the copyright holders (note: not the authors!) in order to gain the right to reproduce all those figures and tables in our book. It is a difficult decision for each and every figure given that the costs vary from approximately $100 to $1000 per figure and there are 99 of them in the book!

Consider the figure shown at the bottom of this post – it illustrates data from some research by Goffman and Malin (1999) in which adults and children produced nonsense words with either a trochaic stress pattern (strong-weak) or an iambic stress-pattern (weak-strong). Kinematic tracings of lower lip movements are shown. The surprise was that the children modulated the stress pattern of the iambic words in a fairly adult-like manner, albeit with less consistency than the adults. The children did not modulate the stress pattern of the trochaic word, producing it like a spondee, with equal stress on both syllables, which was an unexpectedly immature pattern. Why did I choose to keep this figure in a book on phonology? Surely the whole point of phonology is to convert speech to an abstract form like this: [ˈpʌpəp] and [pəˈpʌp]? In the end I decided that I wanted to keep it because I so much want my students to see it – it encapsulates so many primary themes in our book, as follows:

  1. Basic concepts are essential to understand, and for multilingual students in particular, the figure provides a beautiful visual representation of trochee, spondee and iamb that is much more effective than a string of phonetic symbols.
  2. What you get is not always what you hear! If you were to transcribe the child saying the word “puppet” with the kinematics shown in the lower left quadrant of the figure, the odds are that you would produce [ˈpʌpət] which would represent what you expect to hear rather than exactly what the child said. I spend quite a bit of time talking about the limits of phonetic transcription in the first chapter of the book.
  3. The development of prosody is fundamental to the development of phonology: prosodic frames – word templates made up of syllable shapes and stress patterns that are characteristic of ambient language – emerge early and support the acquisition of phonemes. These two levels of the phonological hierarchy are intimately interconnected – it really is time to stop teaching linear phonology.
  4. Phonology is fully dependent upon phonetics – you cannot understand phonological development without understanding the articulatory and perceptual substrates.
  5. Having said that, it is not true that phonological development is determined by maturation of the motor system. If it were, the trochaic pattern would emerge first, before the iambic stress pattern, whereas the reverse is shown in the figure. This demonstration can be the trigger for an interesting discussion of competing approaches to intervention.
  6. The figure is a beautiful illustration of the operation of lexical contrast. Why does the child learn to modulate the strong-strong stress pattern to produce a weak-strong iamb before properly mastering the (for English) canonical strong-weak pattern? Because they must do that in order to produce a contrast between these two word templates in the minds of the listener.
  7. The figure is a lovely illustration of how phonology emerges from the dynamic interplay of phonetic, semantic, and social factors with a dynamic systems approach to development being a coherent thread throughout the book.

The thing about a book however is I can only build possibilities into it – the teaching and the learning is constrained by the imagination of the teachers and the learners. I don’t know how many readers will discover in a paragraph on the development of “interarticulator coordination” a plethora of important messages about the development of phonology.

Figure 3-7

Figure 3–7. Time and amplitude normalized kinematic tracings of displacement of the lower lip during productions of the nonsense words [ˈpʌpəp] (left) and [pəˈpʌp] (right), recorded from an adult (top) and child (bottom). The corresponding spatiotemporal indexes for the repeat productions shown are: (A) adult trochee STI = 8.56, (B) adult iamb STI = 8.99, (C) child trochee STI =18.15, and (D) child iamb STI = 14.24. Adapted from Goffman & Malin (1999). Metrical effects on speech movements in children and adults. Journal of Speech, Language, and Hearing Research, 42, Figure 5, p. 1009. Used with permission of the American Speech-Hearing-Language Association.

References

Rvachew, S., & Brosseau-Lapré, F. (2018). Developmental Phonological Disorders: Foundations of Clinical Practice (Second Edition). San Diego, CA: Plural Publishing. http://pluralpublishing.com/publication_dpd2e.htm

Goffman, L., & Malin, C. (1999). Metrical effects on speech movements in children and adults. Journal of Speech, Language and Hearing Research, 42, 1003-1015

(edited on August 26, 2016 to correct copy-right date for DPD2e. The second edition will be released in December 2016)

Speech and Language Therapy as a Transactional Process

I fell across this very intriguing paper in which the researchers used “bug in ear” devices to reinforce early childhood educators when they used language stimulation techniques with children in the preschool environment, specifically: following the child’s lead, offering the child choices, modeling correct language, waiting for responses, reinforcing desired responses, and expanding the child’s utterances. Three of these behaviors were selected individually for each educator because they did not or rarely used the strategy in practice. The researcher taught the educator to implement the strategy using modeling and role play activities and then deployed the “bug in ear” technology to reinforce use of the strategy while the educator was interacting with a specific child during play sessions in the natural preschool environment. Each strategy was introduced in turn using a multiple baseline single subject design, keeping child constant across each single subject experiment. The children were toddlers with autism spectrum and/or communication disorders. Child outcomes were described in terms of number of communicative attempts per minute whereas educator outcomes were described in terms of number of strategy uses per minute. The results were evaluated using an effect size metric designed for single subject experiments – the “improvement rate difference”. I have made a table of the results below for each of the four educator-child dyads, showing IRDs for the educator and the child during the intervention and maintenance phases, relative to baseline. Note that these verbal descriptions of effect size do not necessarily reflect the source of the effect. However, the raw data presentations of the multiple baseline experiments provide considerable confidence that the “bug in ear” technique was responsible for increases in strategy use by the educators. At the same time, any increases in communicative attempts by the children were not clearly associated with the intervention.

transactional

It can be seen from the table that the educators learned to use the strategies that were taught. The figures in the paper tell a more dramatic story with large and immediate increases in the use of each strategy as it was introduced to the educator by the researchers and reinforced using the “bug in ear” technology. Therefore this technology and the teaching strategies that were used proved to be a very effective option for improving clinical practice by practitioners. Presumably these teaching techniques could be used with our pre-professional students in our clinical programs. However, it was disappointing to see use of the strategies decline markedly after the researchers left the building (notice that IRDs are smaller during the maintenance phase (no bug in ear) than the intervention phase (bug in ear training phase). This is a known phenomenon – many researchers have remarked that extraordinary efforts must be made to maintain use of these strategies by educators. This study provides some clues as to why that might be. It can be seen that educators maintain their use of the strategies while they are receiving external reinforcement for doing so. During the active intervention stage the reinforcement comes from the researchers via the “bug in ear” technology. After the researchers stop providing this “unnatural” reinforcement, one might expect that the children themselves would provide ongoing reinforcements for the use of strategies designed to improve their communication skills. It can be seen here however that “natural” reinforcement is not forthcoming from the environment because the children are not substantially increasing their communicative attempts and most certainly not in direct response to the educators’ efforts.

This outcome reminds me of some old papers by Yoder and colleagues on the transactional nature of communicative exchanges between children with developmental delays and their parents and/or therapists. They were able to show that when prelinguistic milieu teaching changed the child’s behavior (i.e., increase in intentional communication), mothers changed their behavior in response (i.e., increased mapping of linguistic responses to the referent of the child’s communication). This transactional effect occurred even though the mothers were not involved in the direct (and rather directive) intervention that changed the child’s communication behaviors.

Francoise Brosseau-Lapré and I observed a similar effect in our recent study of speech therapy interventions to improve speech accuracy and phonological awareness. The study had multiple phases. Initially the children received individual speech therapy, observed by the parents. Then the parents were taught to implement a home program, in some cases a dialogic reading program in which the parents adopted a more active and directive teaching style when reading books with their child each evening. When this home program was preceded by an input oriented intervention, the dialogic reading intervention was a success, we believe because we first taught the children to listen carefully to speech input and to engage in reciprocal adult-child interactions. Alternatively, when the dialogic reading program was preceded by a traditional articulation therapy program, the parents reported that their children were annoyed by this new style of reading, preferring to be passive while the parent simply read the book. The children who experienced this combination of interventions did not experience as good outcomes as the children who experienced the former combination of interventions. We were unable to follow-up these families due to an unfortunate change in priorities by the funder. However, I strongly suspect the parents whose children were annoyed by dialogic reading would not be motivated to keep it up!

Currently when young children show delays in the development of communication skills it is common to work with the parents, entreating them to learn and increase the use of strategies that come naturally to middle class parents of children with normally developing speech and language. It is critical to understand the role of the child in eliciting and maintaining those behaviors however. Speech and language therapy cannot be expected to be effective without simultaneous attention to the child and the child’s environment.

References

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.

Flowers, H., Girolametto, L., Weitzman, E., & Greenberg, J. (2007). Promoting early literacy skills: Effects of in-service education for early childhood educators. Canadian Journal of Speech-Language Pathology and Audiology, 31, 6-18

Ottley, J. R., & Hanline, M. F. (2014). Bug-in-Ear Coaching: Impacts on Early Childhood Educators’ Practices and Associations With Toddlers’ Expressive Communication. Journal of Early Intervention, 36(2), 90-110. doi:10.1177/1053815114563614

Wasik, B. A., Bond, M. A., & Hindman, A. (2006). The effects of a language and literacy intervention on Head Start children and teachers. Journal of Educational Psychology, 98(1), 63-74.

Yoder, P.J., Warren, S.F., Kim, K. & Gazdag, G.E. (1994). Facilitating prelinguistic communication skills in young children with developmental delay II: Systematic replication and extension. Journal of Speech and Hearing Research, 37, 841-851.

Acquisition of Fricatives in Icelandic and French

I point out in this blog a recent paper by Bernhardt and colleagues describing fricative production by Icelandic preschoolers with “protracted phonological development”. Icelandic-speaking children with speech problems produced /f,s,θ/ with about 70% accuracy by four years of age. The English-speaking children with speech problems achieved less than 15% accuracy on the single word naming task (those of us who work with those children are not surprised!). Error patterns were different as well (for example, the Icelandic children substituted [t] for /f/ whereas the English children substituted [p] for /f/). The study is a nice reminder of the need for language specific articulation tests for children with intelligibility problems whose first language is not the majority language. There are no universal developmental patterns. Therefore we can be grateful to Sharynne McLeod and the International Working Group on Multilingual Children’s Speech for their great site.

A point of theory in the paper was the failure to support the hypothesis of “higher overall fricative accuracy for English, because English has more fricative types.” This hypothesis was put forward because Edwards, Beckman and Munson concluded that “the more words containing a sound that a child has learned to say, the more practiced the child becomes at recognizing and reproducing the sound abstracted away from the phonological contexts of a few specific words.” One example given is the case of /ð/ in English. I was surprised that an alternative hypothesis, considering the prosodic structure of Icelandic, was not tested. Perhaps the authors didn’t want to attempt this because it is so hard to understand the prosodic structure of Icelandic! I certainly will not try to do this. However I point out that French and Icelandic are characterized by earlier acquisition of fricatives compared to English:

Acq of Fric

Françoise and I have previously pointed out that the prosody of French helps children learn the segments. Several studies now confirm that French-speaking children learn consonants early: they have a complete consonant repertoire at an early age and they master accurate production of the consonants at an early age (compared to English). Furthermore, French-speaking children with speech problems produce more syllable structure and fewer segmental errors (compared to English-speaking children with speech problems). How does the prosody of French explain these findings? French is a syllable timed language with a tendency toward long words made of several syllables having equal stress. The syllables tend to have a simple CV structure even though complex onsets and codas are allowed. The difference between the two languages can be observed in the ratio of consonants to vowels, being 1.6 in French and 2.1 in English.

Recall that when children first learn to speak, they learn to produce “whole words” and not strings of individual segments; these first whole words act as templates for the production of more words. These initial templates are often made up of reduplicated or partially reduplicated syllables. Possibly, if the initial word shape template is easy to learn or construct, more processing power is left over to acquire the segments inside the syllables. Furthermore, simple stressed syllables in French may increase the perceptual salience of those segments. Vihman provides wonderful examples of this process in her very excellent paper on templatic phonology. The French child, Gael, saying words like ‘accroché’ [χʁoʃe] at age 21 months is rather fun to see!

Possibly the same process occurs in Icelandic which has a very particular prosody that may also increase the perceptual salience of postvocalic consonants, fricatives in particular. I will not attempt an explanation, the phonology of Icelandic being quite beyond me, but any explanation for the early acquisition of these phonemes must take the prosodic (word shape) characteristics of early child input into account.

In the meantime some more general points strike me. It is impossible for us as speech-language pathologists or academics to understand the process of speech development without data and it is disheartening how little data there is on these languages. Basic information such as the types and tokens of fricatives that are presented to children in the input across languages is difficult to find. We need to know much more about the prosody of all these languages but prosody receives scandalously little attention compared to, for example, consonants.

We also need to know more about the processes by which children select and construct their early word templates. This requires painstaking small sample detailed longitudinal work and large, large sample laboratory work using creative paradigms, some probably not invented yet. However, all our work is perilously underpowered and underfunded.

Finally we need huge diversity in academia – lots and lots of movement of students across the world, bringing new techniques to new languages. Unfortunately in the past few days, in the aftermath of Brexit, I have encountered many depressing conversations on the internet about the control of borders. Even in the domain of “highly qualified personnel”, some graduates are deemed more worthy than others and we all know where the humanities fall on the ranking! I prefer not to counter this sort of thinking with purely utilitarian arguments, but clearly it is short sighted given the importance of communication and communication disorders. On a more positive note I close by congratulating the excellence of child phonology projects sustained on a wing and a prayer such as the Cross-linguistic Child Phonology Project led by Bernhardt and colleagues and also the Paidologos project led by Edwards and colleagues.

 

References

Bernhardt, B. M., Másdóttir, T., Stemberger, J. P., Leonhardt, L., & Hansson, G. Ó. (2015). Fricative acquisition in English- and Icelandic-speaking preschoolers with protracted phonological development. Clinical Linguistics & Phonetics, 29(8-10), 642-665. doi:10.3109/02699206.2015.1036463

Brosseau-Lapré, F., & Rvachew, S. (2014). Cross-linguistic comparison of speech errors produced by English- and French-speaking preschool age children witih developmental phonological disorders. International Journal of Speech-Language Pathology, 16(2), 98-108.

Edwards, J., Beckman, M. E., & Munson, B. (2015). Frequency effects in phonological acquisition. Journal of Child Language, 42(02), 306-311. doi:doi:10.1017/S0305000914000634

MacLeod, A. A. N., Sutton, A., Trudeau, N., & Thordardottir, E. (2011). The acquisition of consonants in Québec French: A cross-sectional study of preschool aged children. International Journal of Speech-Language Pathology, 13, 93-109.

Rvachew, S., Marquis, A., Brosseau-Lapré, F., Paul, M., Royle, P., & Gonnerman, L. M. (2013). Speech articulation performance of francophone children in the early school years: Norming of the Test de Dépistage Francophone de Phonologie. Clinical Linguistics & Phonetics, 27(12), 950-968. doi:doi:10.3109/02699206.2013.830149

It Makes a Difference What We Do

In a recently published study, Farquharson et al. demonstrated that individual SLPs, working in the school environment, make a significant contribution to one-year gains in grammar, vocabulary and word decoding: specifically, percentage of variance attributable to the SLP was 11%, 8% and 12% for these three domains respectively. Unfortunately however these researchers were unable to account for these between-SLP differences in effectiveness since years of experience, caseload size and other time pressures did not significantly explain child outcomes.

I have previously described data on phonology treatment outcomes by individual SLP that we reported from a randomized control trial (shown in the table below). These data  similarly indicate that different SLPs achieve different outcomes; in this case, the between SLP effect was observed even when treatment approach and intensity were held constant. You can see that on average children obtained the best outcome in the ME condition (earlier developing stimulable targets) compared to the LL condition (later developing unstimulable targets). However, SLP 4 obtained rather poor outcomes in both conditions and SLP 3 obtained good outcomes in both conditions.Ebert and Kohnert reanalyzed this table and concluded that the SLP accounted for 20% of the variance in outcomes in this study designed to assess the impact of different approaches to target selection.

Rvachew, Nowak 2001 Table 4

So the question is, if experience, time pressure, and intervention decisions do not account for these differences in outcome that are attributable to the SLP, what makes one SLP more effective than another? It is unfortunate that there is no systematic program of research on this question in the SLP field but we can turn to the education literature for clues. Similarly, the vast literature on teacher effectiveness finds that teacher training and years of experience per se do not account for between-teacher differences in classroom outcomes even though teachers have a large impact on their pupils’ learning. More nuanced investigations have found however that teacher competence does explain outcomes in specific domains when measured in terms of specific experience and training. Therefore teachers who have more years of experience teaching first grade, extra formal training in the teaching of reading, and/or demonstrably greater knowledge of literacy concepts can have a significant positive effect on reading outcomes (see Johanson et al, 2015; Piasta et al, 2009).

Despite the regrettable lack of research that definitively identifies the characteristics of effective SLPs, the studies on teacher effectiveness suggest to me that it would be wise to formalize a system of specialisation among speech-language pathologists. Academics have been talking about this for a very long time as I distinctly remember sitting at the “speaker’s table” over thirty years ago during a banquet at which the gentleman seated next to me expounded for a good part of the evening about the need for a formal specialty in fluency disorders. I have forgotten the name of said gentleman who saw no reason to have specialization for phonology! I of course did not agree – phonological disorders, school speech-language pathology, language learning impairments and so on are at least as complex as fluency or dysphagia or aphasia. In any case, in all of these areas of speech-language pathology practice, specialist knowledge of the underlying theory and concentrated experience in the application of that knowledge will improve outcomes for the children and adults that we serve. For some reason the idea has never really taken off in the clinical community but I would be very happy if the certification boards or regulatory bodies would take it up.

Another message that I draw from Farquharson et al.’s interesting study is that it makes a difference what we do! Sometimes we get so weighed down by factors outside our control – excessively large caseloads, administrative interference in treatment choices, increasingly complex cases and so on – that it is easy to forget this. Digressing back to the studies on teacher effectiveness, another variable that comes up frequently is attitude – teachers who believe in their own self efficacy and in their pupils’ capacity for growth get the best outcomes. I am sure that the same is true for SLPs and therefore I repeat the point when I can, it really does make a difference what you do.

References

Ebert, K., & Kohnert, K. (2010). Common factors in speech-language treatment: An exploratory study of effective clinicians. Journal of Communication Disorders, 43, 133-147.

Farquharson, K., Tambyraja, S., Logan, J., Justice, L. M., & Schmitt, M. B. (2015). Using hierarchical linear modeling to examine how individual SLPs differentially contribute to children’s language and literacy gains in public schools. American Journal of Speech-Language Pathology, 24, 514-516.

Johansson, S., Myrberg, E., & Rosén, M. (2015). Formal teacher competence and its effect on pupil reading achievement. Scandinavian Journal of Educational Research, 59, 564-582.

Piasta, S. B., Connor, C. M., Fishman, B. J., & Morrison, F. J. (2009). Teachers’ Knowledge of Literacy Concepts, Classroom Practices, and Student Reading Growth. Scientific Studies of Reading, 13(3), 224-248.

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.

Rvachew, S. (2015). Testing combinations of phonological intervention approaches for francophone children. Behind the Science podcast. CREd Library.

Speech Perception and Persistent Speech Errors

Jon Preston is in my opinion the most interesting researcher to watch in the field of speech sound disorders. His recent studies on structural and functional brain differences in older children with persistent speech errors are very interesting. The two studies complement each other and point to structural and functional differences in supra superior temporal gyrus, consistent with repeated findings of perceptual deficits in children with speech deficits. Additional differences in supramarginal gyrus implicate integration of auditory and somatosensory information during feedback processes that are important for learning to produce speech sounds as well as monitoring and fine-tuning speech sound production as the articulatory system matures.

Given these neuroimaging findings, it makes sense to look for behavioral indices of perceptual difficulties in this population of children with persistent speech sound errors. Recently Preston et al (2015) used SAILS to do this with two different groups of school aged children. SAILS is a tool that I developed for speech therapy with preschoolers. Each module consists of natural speech recordings of adults and children producing a word that begins with a commonly misarticulated phoneme, for example, the word “rat”. Half the words are produced correctly and the remainder are misarticulated, e.g., [wæt], [jæt], [ɹ̮æt]. Each module is designed as a series of blocks in which the contrasts are theoretically closer, e.g., practice [ɹæt] versus [mæt], block 1 [ɹæt] versus [wæt], [jæt] and block 2 [ɹæt] versus [ɹ̮æt].  The child’s task is to identify the words that are “good” representatives of the target word. Although the blocks are numbered, they do not necessarily fall into a linear difficulty scale because each child can be quite idiosyncratic in terms of the features that they attend to. I’ll come back to this point later. After establishing that the tool was effective as an intervention for improving children’s speech perception and speech production skills, I found that it also had some value as an assessment tool (Rvachew & Grawburg, 2006) although I do not feel that the psychometric qualities are particularly good and I certainly did not design it for that purpose.

Now, back to Jon Preston’s study. In the first study, older children with [ɹ] distortions were compared to children with correctly produced [ɹ] and no history of speech delay. They were administered only the “most difficult” levels of SAILS modules including the [ɹ] Level 2 module. Although 1/20 children with typical speech and 6/27 misarticulators failed the [ɹ] SAILS module, the mean difference between groups was not significant. In the second study, a group of 25 children who received speech therapy as preschoolers was tested with SAILS, 3 years later when the speech deficit was resolved except in some cases for a persistent speech sound distortion. Performance on the “most difficult” [s] or [ɹ] module was correlated with their performance on an [s] or [ɹ] production probe. There was no correlation. (I was initially mystified by the perception results because they didn’t look like anything I had seen before but that was before I realized that the children were not presented with the complete test!).

So, how do we interpret these results? I have three comments.

First, Preston, Irwin, & Turcios have done us all a good turn by establishing that SAILS is NOT a good tool for assessing speech perception in 7 to 14 year old children with persistent speech errors. I never intended it for that purpose and I am pleased to have empirical evidence that supports a clear answer to the question when it comes up (we should be grateful to Seminars in Speech and Language for publishing it I suppose, despite the small samples, because rumour has it that ‘negative results’ are hard to publish). Anyway, we need something better for testing speech perception, especially for older children. I invite reader comments on what that “something better” would be. We know from many studies using synthetic speech that this population is at risk for perceptual deficits. We need to be able to identify those children in the clinic.

Second, if you are going to use SAILS for assessment (with children aged 4 to 7) it is very important to administer the complete module to the child, working through all the levels of the module, in order as intended. We cannot be sure that the child’s response to, for example Level 3 /s/, will mirror that of the normative samples who encountered Level 3 after first working through Practice, Level 1 and Level 2 before getting there. I will come back to this in another post in which I will give a sneak peek at the upcoming second edition of our book Developmental Phonological Disorders: Foundations of Clinical Practice.

Third, the relationship between speech perception and speech production is not linear. Even though I have found relationships between speech perception and speech production in the past using some rather fancy statistics with large groups (Rvachew & Grawburg, 2007; Rvachew, 2006), I cannot at the individual child level relate in a simple fashion SAILS score with number of correct productions of a phoneme. The reason is that the child’s production and perception of a phoneme is related to the way in which the child attends to the features associated with phoneme contrasts and certain features have different information value for perception versus production. We give an example of this in Chapter 4 of DPD (from Alyssa Ohberg’s masters thesis): preschoolers who were stimulable for /θ/ and /s/ but had not mastered this contrast were administered the SAILS /θ/ assessment module. Some children, in their speech, differentiated /s/-/θ/ by manipulating the duration cue whereas others differentiated /s/-/θ/ by manipulating the spectral cue; as you would expect, manipulating the spectral cue resulted in comparatively better articulatory accuracy but these two groups produced roughly comparable perceptual performance but with some interesting differences. The children who attended to the spectral cue actually did better on the supposedly “harder” level 3 stimuli than the supposedly “easier” level 2 stimuli, highlighting again that there is not a linear difficulty gradient across the stimulus blocks. The children who attended to the duration cue did surprisingly well at levels 2 and 3.  For some stimuli, attention to the duration cue actually provides an advantage. This results occurs because duration is actually a pretty reliable cue for perception of /θ/ but it does not provide any information that helps the child achieve the critical articulatory gestures (e.g., grooved versus nongrooved tongue,interdental versus alveolar tongue tip placement). In this case, there is no direct linear relationship between the child’s speech perception score and their speech production score on the tests that we gave. However, there is a direct relation between the child’s perceptual focus on only one of the relevant acoustic cues and their inability to produce the phoneme correctly. The only children who achieved good perception scores and good production scores attended to both the duration and the centroid cues.

This example raises a fourth point and that is, drawing on Shuster’s findings, the best test for older children may well involve using the child’s own speech production output. The most important question is, does the child mistakenly believe that their own productions are accurate and acceptable representations of the target category? I cannot recommend Shuster’s brilliant study highly enough for anyone treating this population. If the child does prove to have incomplete perceptual knowledge of /ɹ/ or /s/ however, treatment that includes highly variable (multi-talker) stimuli remains important, as a general rule of perceptual learning.

Further Reading

Preston, J. L., Felsenfeld, S., Frost, S. J., Mencl, W. E., Fulbright, R. K., Grigorenko, E. L., . . . Pugh, K. R. (2012). Functional Brain Activation Differences in School-Age Children With Speech Sound Errors: Speech and Print Processing. Journal of Speech, Language, and Hearing Research, 55(4), 1068-1082. doi: 10.1044/1092-4388(2011/11-0056)

Preston, J. L., Molfese, P. J., Mencl, W. E., Frost, S. J., Hoeft, F., Fulbright, R. K., … & Pugh, K. R. (2014). Structural brain differences in school-age children with residual speech sound errors. Brain and Language, 128(1), 25-33.

Preston, J. L., Irwin, J. R., & Turcios, J. (2015). Perception of Speech Sounds in School-Aged Children with Speech Sound Disorders. Seminars in Speech and Language, 36(04), 224-233. doi: 10.1055/s-0035-1562906

Rvachew, S. (2006). Longitudinal prediction of implicit phonological awareness skills. American Journal of Speech-Language Pathology, 15, 165-176.

Rvachew, S., & Grawburg, M. (2006). Correlates of phonological awareness in preschoolers with speech sound disorders. Journal of Speech, Language, and Hearing Research, 49, 74-87.

Shuster, L. I. (1998). The perception of correctly and incorrectly produced /r/. Journal of Speech, Language, and Hearing Research, 41, 941-950.

 

 

 

 

 

 

Do babies perceive speech with their tongues?

Recently Alison Bruderer (a post-doctoral fellow in Janet Werker’s lab) reported to @ASHAweb that impediments to infants’ tongues movements impair their ability to perceive speech, concluding further that her results, published in PNAS, support the motor theory of speech perception. Tara McAllister Byun (@byunlab) has commented on social media quite adequately in her own right but has asked me to follow up with a blogpost since we share the same concerns, so here I go! This is the long version of Tara’s complaint.

Some background about infant speech perception testing is required. Infant speech perception research exploded after Peter Eimas and colleagues perfected a technique called the high amplitude sucking procedure in the early 1970s. With this procedure, the infant sucks on a special soother while specific speech input is provided to the infant contingent upon a criterion rate of sucking; there is an initial increase in the infant’s sucking rate followed by a decline as the infant habituates to the stimulus; subsequent to habituation, a new stimulus is introduced and an increase in the infant’s sucking rate is interpreted as evidence that the infant discriminates the new stimulus from the initial input. As shown in the picture (borrowed from Scientific American, scandalously without permission!), you can see that the infant must be able to perceive speech with the tongue fully occupied in order to succeed at this experiment. And indeed they did – Eimas demonstrated that newborn infants can perceive many contrasts and everyone was so excited by this that textbooks to this day claim that all infants can perceive all the phonetic contrasts of all the world’s languages at birth even though this is not at all true notwithstanding the fact that infant speech perception abilities are indeed remarkable.Scientific American HAS

Since that time many new test techniques have been developed, some employing this idea of habituation in one form or another and others using reinforcement of specific responses to speech input. What do we know from thousands of studies since published? Infants can indeed perceive many contrasts but not all of them. Some contrasts are much easier for infants to perceive than others – for example fricative contrasts remain difficult to perceive throughout infancy and corner vowels are more salient than central vowels. The specific acoustic characteristics of the stimuli relative to the infant’s experience are very important and impact the infants’ performance in surprising ways. Infant performance is highly vulnerable to memory and attention constraints and many infants, sometimes the majority tested, do not complete the test procedures. Test-retest performance for individual babies is close to zero.  The procedures are so finicky that when Nittrouer pointed out that that many infants cannot perceive fricative contrasts, she was criticised for testing the infants in a high chair, rather than in their mothers’ laps as is customary in other labs! Infant perception is shaped by environmental speech input such that perceptual sensitivity for native language contrasts is enhanced while perceptual sensitivity for foreign language contrasts declines during the first year of life. There are discontinuities in perceptual performance during development as perceptual knowledge is integrated with other linguistic skills, so that for example, the ability to perceive phonetic contrasts seems to disappear and then reappear around 12 months of age as the infant reorganizes perceptual knowledge to serve the process of word recognition.

The procedure used by Bruderer involves presenting the infant with a series of alternating and nonalternating trials in which some stimuli are different versions of the same phonetic category and other stimuli come from different phonetic categories, like this:

trials bruderer werkerThere are actually 8 trials but the point is nonalternating (Nalt, 2 stimuli from the same category such as dental) and alternating (Alt, 2 stimuli from different categories such as dental vs retroflex) trials are interleaved across the experiment so that the infant’s behavior can be compared for these two trial types, in pairs (i.e., trial 1 vs trial 2 is pair 1 and so on). The behavior that is recorded is “looking time”. It is assumed that if the infant looks at a checkerboard pattern longer when hearing Alt trials, in comparison to Nalt trials, then the infant can hear the difference between the stimuli during the Alt trials. You also expect that looking times will generally decline over the experiment. So you hope to see results as shown in the figures below. I had to make these up because of paywalls on the relevant articles but the left figure is similar to what Bruderer found for 6 month old infants in her experiment (they can perceive the foreign language contrast as revealed by divergence in the lines) and the right figure is similar to what Yeung and Werker found for 9 month old infants (they can no longer perceive the contrast as revealed by overlapping lines).

Bruderer Werker simulated results

Hypothetical but realistic 6 mo vs 9 mo looking times (no teethers)

So now we can ask what you would expect if putting a teether in the infant’s mouth interfered with perception because… motor theory of speech perception! I would expect looking times on Alt trials to be low and overlapping with looking times for Nalt trials, as in the figure on the left. What actually happened? When a flat teether was put in the infants’ mouths, looking times for both Alt and Nalt trials started very high and then dropped steadily over the remaining three pairs of trials, overlapping to give the impression that the infants could not discriminate the stimulus pairs in the Alt trials. Then they ran a different group of infants with a “gummy” teether in their mouths – in this case tongue movement was not inhibited. Here, looking time was high during pairs 1, 2, and 3 and dropped during pair 4 but only in the Nalt condition; therefore the lines diverged in pair 4. In other words it looks as if teethers cause looking times for Nalt trials to go up, rather than looking times during Alt trials to go down!  I can’t actually prove that because you cannot really compare across groups of babies in this study. But, the researchers’ conclusions are based on a comparison of p values across the 3 groups of babies: when looking times across trials types are compared for each group of babies the following statistical results were reported: Group 1 (no teether) F(1,23) = 4.32, P = 0.049; Group 2 (flat teether) F(1,23) = 0.011, P = 0.92; and Group 3 (gummy teether) F(1,23) = 5.26, P = 0.031). Comparing Group 2 with 3 they conclude that inhibiting tongue movements impairs speech perception.

What are the reasons to be cautious about the interpretation of these results? The first issue is that the conclusions are drawn by essentially comparing the p value obtained for Group 2 with the p value obtained for Group 3, and concluding the two groups are different, not a safe assumption (see Gelman and Stern on this point). There is no direct evidence that the behavior of the infants between these two groups is substantially and significantly different. Further to the interpretation, it is difficult to be sure what the infants are perceiving or not perceiving as they participate in this task. Recall that our perception is intimately related to attentional factors – in fact our brains do not lose the ability to perceive foreign language phonetic contrasts, we learn to ignore them, as is elegantly shown by Choeur’s ERP studies. The introduction of the teethers appears to change the habituation behavior of the infants in the study and thus it is not clear how to interpret their looking time. Possibly the teethers shift attention to somatosensory feedback and looking time indexes those perceptual inputs, and nothing at all about speech perception abilities. Alternatively, the teethers may enhance overall arousal in such a way that the infants are actually as sensitive to the within category differences (Nalt trials) as they are to between category differences (Alt trials) in speech sounds. Thirdly, it is possible, that at 6 months of age there is a temporary disruption in speech perception in the flat teether condition that reflects an emerging link between brain areas for perception and speech production that Kuhl says is activated by speech practice in babbling. In this case I am taking the reported results at face value but I am not accepting that they are evidence for the motor theory of speech perception which posits that the objects of speech perception are innately the articulatory gestures themselves. In any case, many more studies with varying design and analysis strategies are required before we can be sure of the interpretation of these intriguing findings. Once again Janet Werker’s lab is at the forefront of an exciting new area of infant research.

References

Aslin, R.N., Werker, J.F., & Morgan, J.L. (2002). Innate phonetic boundaries revisited. J. Acoust. Soc. Am. 112, 1257 (2002); http://dx.doi.org/10.1121/1.1501904

Bruderer, A. G., Danielson, D. K., Kandhadai, P., & Werker, J. F. (2015). Sensorimotor influences on speech perception in infancy. Proceedings of the National Academy of Sciences, 112(44), 13531-13536. doi: 10.1073/pnas.1508631112

Cheour, M., Ceponiene, R., Lehtokoski, A., Luuk, A., Allik, J., Alho, K., & Näätänen, R. (1998). Development of language-specific phoneme representation in the infant brain. Nature Neuroscience, 1, 351-353.

Cristia, A., Seidl, A., Singh, L., & Houston, D. (2016). Test-retest reliability in infant speech perception tasks. Infancy, Early View, 1-20.

 

Eimas, P. D. (1985). The perception of speech in early infancy. Scientific American, 252, 46-52.

Gelman, A., & Stern, H. (2006). The difference between “significant” and “not significant” is not itself statistically significant. The American Statistician, 60(4), 328-331,DOI: 310.1198/000313006X000152649.

Imada, T., Zhang, Y., Cheour, M., Taulu, S., Ahonen, A., & Kuhl, P. K. (2006). Infant speech perception activates Broca’s area: a developmental magnetoencephalography study. Neuroreport, 17, 957-962.

Kuhl, P. K. (2004). Early language acquisition: Cracking the speech code. Nature Reviews: Neuroscience, 5, 831-843.

Nittrouer, S. (2001). Challenging the notion of innate phonetic boundaries. Journal of the Acoustical Society of America, 110(3), 1598-1605.

Mattock, K., Polka, L., Rvachew, S., & Krehm, M. (2010). The first steps in word learning are easier when the shoes fit: comparing monlingual and bilingual infants. Developmental Science, 13, 229-243.

Yeung, H. H., & Werker, J. (2009). Learning words’ sounds before learning how words sound: 9-month-olds use distinct objects as cues to categorize speech information. Cognition, 113, 234-243

CAMs & Speech Therapy

In this final post on the potential conflict between Evidence Based Practice (EBP) and Patient Centred Care (PCC) I consider those situations in which your client or the client’s family persists in a course of action that you may feel is not evidence based. This is a very common occurrence although you may not be aware of it. Increasing numbers of surveys reveal that the families of children with disabilities use Complementary and Alternative Medicines/Therapies (CAMs), usually without telling their doctor and other health care providers within the “standard” health care environment.

Despite a growing number of studies it is difficult to get an exact estimate of the prevalence of CAM use among such families (see reading list below). Some estimates are low because families are reluctant to admit to using CAMs. Other estimates are ridiculously high because CAM users are responding to insurance company surveys in order to promote funding for these services and products. However, the best estimates are perhaps as follows: about 12% of children in the general population are exposed to CAMs; the proportion probably doubles for children with developmental disabilities in general and doubles again for children with autism. The most commonly used CAMs are dietary supplements or special diets, followed by “mind and body practices” (sensory integration therapy, yoga, etc.); the use of dangerous practices such as chelation therapy is mercifully much less frequent. Predictors of CAM use are high levels of parental education and stress. The child’s symptoms are not reliably associated with CAM use. The hypothesized reasons for these correlations are that educated parents have the means to find out about the CAMs and the financial means to access them. Having had some personal experience with this, I think that educated parents are very used to feeling in control of their lives and nothing shatters that sense of control as much as finding that your child has a developmental disability. I find it very interesting that the studies shown below counted CAM use after specifically excluding prayer! I may be wrong but I expect that many well educated parents, even those that pray, would look for a more active solution than putting their family exclusively in the hands of God. Educating yourself through internet searches and buying a miracle cure feels like taking back control of your life (although months later when you realize you have thousands of dollars of worthless orange gunk in your basement, you are feeling out of control again AND stupid, but that is another story). Anyway, this is why I think (an untested hypothesis I admit) that patient centred care is actually the key to preventing parents from buying into harmful or useless therapies.

When the parent asks (or demands, as used to happen when I had my private practice) that you use a therapy that is not evidence based, how do you respond in a way that balances evidence based practice with patient centred care?

The most important strategy is to maintain an open and respectful dialogue with the family at all times so that conversation about the use of CAMs can occur. Parents often do not reveal the use of these alternative therapies and sometimes there are dangerous interactions among the many therapies that the child is receiving. It is critical that the parent feels comfortable sharing with you and this will not occur if you are critical or dismissive of the parents’ goals and choices. A PCC approach to your own goal setting and intervention choices will facilitate that dialogue. It is actually a good thing if the parent asks you to participate in a change in treatment approach.

Find out what the parent’s motivations are. Possibly the parent’s concerns are not in your domain. For example dad might ask you to begin sessions with relaxation and breathing activities. You launch into a long lecture about how these exercises will not improve speech accuracy. It turns out that the exercises are meant to calm anxiety, a new issue that has arisen after a change in medication and some stresses at school. As an SLP, you are not actually in a position to be sure about the efficacy of the activity without some further checking and going along with the parent is not going to hurt in any case.

Consider whether your own intervention plan is still working and whether your own goals are still the most pertinent for the child. Sometimes we get so wrapped up in the implementation of a particular plan we miss the fact that new challenges in the child’s life obligate a course correction. Mum feels like her child needs something else and looks around for an alternative. After some discussion you may find that switching your goal from morphosyntax to narrative skills might work just as well as introducing acupuncture!

Talk with the parent about where the idea to use the CAM came from and how the rest of the family is adapting to the change. It is possible that mum knows the diet is unlikely to work but dad and dad’s entire family has taken it on as a family project to help the child. In some ways the diet is secondary to the family’s sense of solidarity. On the other hand mum may be isolating herself and the child from the rest of the family by committing to an intervention that everyone else thinks is bonkers! This will be difficult but efforts to engage the family with counseling might be in order.

Explore ways to help the parent establish the efficacy of the CAM. With the family’s consent you might be able to find information about the alternative approach from sources that are more credible than google. You might be able to help the parent set up a monitoring program to document changes in behavior or sleep habits or whatever it is that the parent is trying to modify. You may even be able to implement a single subject randomized experiment to document the efficacy of the therapy for the child. Dad may enjoy helping to plot the data in a spreadsheet.

Finally and also crucially, model evidence based thinking in all your interactions with the family. When you are suggesting new goals or approaches to intervention explain your decisions. Involve the family in those choices, describing the potential benefits and costs of the various options by referencing the scientific literature. Let the parent know that you are making evidence based hypotheses all the time and watching their child carefully to confirm whether your hypotheses were correct. Involve families in this process so that they become used to thinking in terms of educated guesses rather than phony certainties.

Reading list

Bowen, C. & Snow, P. C. (forthcoming, about January 2017). Making Sense of Interventions for Children’s Developmental Difficulties. Guildford: J&R Press. ISBN 978-1-907826-32-0 

Levy, S. E., & Hyman, S. L. (2015). Complementary and Alternative Medicine Treatments for Children with Autism Spectrum Disorders. Child and Adolescent Psychiatric Clinics of North America, 24(1), 117-143.

Owen-Smith, A. A., Bent, S., Lynch, F. L., Coleman, K. J., Yau, V. M., Pearson, K. A., . . . Croen, L. A. (2015). Prevalence and predictors of complementary and alternative medicine use in a large insured sample of children with Autism Spectrum Disorders. Research in Autism Spectrum Disorders, 17, 40-51.

Salomone, E., Charman, T., McConachie, H., Warreyn, P., Working Group 4, & COST Action “Enhancing the Scientific Study of Early Autism”. (2015). Prevalence and correlates of use of complementary and alternative medicine in children with autism spectrum disorder in Europe. European Journal of Pediatrics, 174, 1277-1285.

Valicenti-McDermott, M., Burrows, B., Bernstein, L., Hottinger, K., Lawson, K., Seijo, R., . . . Shinnar, S. (2014). Use of Complementary and Alternative Medicine in Children With Autism and Other Developmental Disabilities: Associations With Ethnicity, Child Comorbid Symptoms, and Parental Stress. Journal of Child Neurology, 29(3), 360-367.