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.

 

 

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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.

 

 

 

Thinking about ‘Dose’ and SLP Practice: Part III

Continuing my discussion about the concept of ‘dose’ as applied to speech therapy, I finally get to the heart of the matter which is the issue of the optimal ‘dose’ of speech therapy to achieve the desired outcome which in our context is generalization of a phonology goal to untreated words. In previous blogs I discussed the definition of ‘dose’ in terms of the number of effective teaching episodes and the need to identify the effective ingredients of your intervention beyond the therapeutic alliance. Here I will discuss ‘dose’ specifically, as in how many effective teaching episodes are enough to achieve a good outcome in phonology intervention?

Let’s begin by returning to the pharmacology context from which the concept of dosage is borrowed. How is the concept helpful to physicians? First, it is important to know the optimum dose (or dose range) for average patients so as to avoid harming the patient. If the prescribed dose is too low the patient may not improve and the continuance or worsening of symptoms and disease will be harmful for the patient. If the dose is too high the medication itself may be toxic and harm the patient directly. Second, the patient’s response to the medication is diagnostic. If the maximum safe dosage has been prescribed and the patient is not responding favorably the physician must seek the reason: Is the patient complying with the prescribed treatment regimen? Is the patient doing something else that interferes with the effectiveness of the medication? Is the health care system administering the dose as prescribed? Does this patient respond to medications in an individualized fashion, such that a switch to another medication is required? Is the diagnosis wrong such that an entirely different treatment is called for? I will describe the research on appropriate dose in the case of meaningful minimal pairs therapy (applied to preschool aged children with moderate or severe phonological disorders) and we can consider whether these questions are relevant in the speech therapy context.

The method of meaningful minimal pairs is a uniquely linguistic approach to therapy that has the goal of changing the child’s production of an entire sound class. The procedure has two key components: (1) teaching the child pairs of words that differ by a single phoneme; and (2) arranging the environment so that the child experiences a communication breakdown if both words in a  pair are produced as a homophone. (SLPs and researchers usually get the first part right but often forget the second!) The method is directed at the child’s phonological knowledge and therefore should not be applied until after phonetic knowledge of the contrasting phonemes in the perceptual and articulatory realms has been established.

There is a lot of research involving this method and at least two papers have carefully documented the dose that leads to generalization from trained to untrained words/targets. More than 50% generalization is the outcome of interest because we know from other studies that you can discontinue direct treatment on the target pattern at this point and the child will continue to make spontaneous gains. The two papers that I will discuss have the further benefit of allowing the reader to count the “dose” precisely as the number of practice trials. The papers also provide information about the number of sessions and the number of minimal pairs over which the practice trials were distributed.

Weiner (1981) demonstrated that the method was effective with two children, using a multiple baseline design and treating deletion of final consonants (DFC), stopping of fricatives (ST) and fronting (F). Four minimal pairs were taught per target pattern and use of the pattern was probed continuously for treatment words and on a session-by-session basis for generalization words. The results do not show that much difference across target patterns but the response across children was markedly different with one child showing much faster progress than the other for all targets. For example, Child A reduced DFC to below 50% in treated words after 120 practice trials and in generalization words after 300 trials. On the other hand, Child B required 200 and 480 trials respectively to reach the same milestones for DFC. Furthermore Child A was able to accomplish many more trials in a session (e.g., 400 practice trials over 5 sessions for child A or 80 trials/session vs. 570 practice trials over 13 sessions or 43 trials/ session for child B). Despite this large variance in rate of progress across children, the study suggests that an SLP should expect a good treatment response with this method after no more than 500 trials.

This finding was replicated in a larger sample (n = 19) by Elbert, Powell and Swartzlander (1991). In this study a behaviorist approach was taken to the treatment of the minimal pair words in contrast to Weiner’s procedure that emphasized the communication breakdown as an important part of the procedure. The children were taught one pair at a time in series and the study was structured to determine how many children would achieve generalization to untreated words ,at a level of at least 50%, after learning 3, 5 or 10 pairs of words. They found that 59% of the children generalized after learning 3 pairs which took an average of 487 practice trials (range 180 to 1041) administered over approximately 5 20-minute treatment sessions; 21% of children needed to learn 5 word pairs (1221 practice trials on average) and 14% needed to learn 10 words pairs (2029 practice trials on average) before generalization occurred. This left 7% of children who did not generalize at all.

How can we use these data about dosage in our treatment planning? There is a lot of useful information here. First, we know that it is possible to achieve 80-100 practice trials in 20 minutes. Therefore, if your treatment sessions are 20 minutes long you can target one phonological pattern and if they are 60 minutes long you can target 3. Second, they show us that children do not usually generalize in under 180 practice trials (and I would argue that the data indicate that it is number of practice trials rather than sessions that is important). What harm might arise if you provide a child with the government mandated 6 annual treatment sessions, targeting three patterns, but failing to achieve more than 100 practice trials for each target pattern across the 6 sessions? We can predict that the child will not start to generalize before the end of the block and therefore will not continue to make spontaneous gains after treatment stops. When the next block begins the child may be discouraged and less cooperative with the next SLP. The parent may become discouraged and seek out complementary or alternative interventions that are even more useless or harmful than speech therapy provided with insufficient intensity!

What if the child has achieved more than 500 practice trials and has not generalized? At this point you have more than enough reason to reassess your diagnosis and/or your approach. Child B in Weiner’s study for example did finally achieve many practice trials but did so slowly because he was unable to achieve the recommended intensity, producing much fewer than 80 practice trials per session. This child also failed to generalization after 500 trials for one of his targets. Perhaps this child was lacking in the necessary prerequisites such as stable perceptual and articulatory representations for the target phonemes. Or, perhaps the child viewed the communication breakdowns to be the SLP’s listening problem rather than his own speech problem and thus a disconnect at the level of the therapeutic alliance was hampering the child’s learning.  What about the children in Elbert et al who did not generalize at all? It was eventually revealed in the paper that these children presented with many “soft signs” indicative of both speech and oral motor apraxia. Therefore, continuing to almost 3000 practice trials for these children was most assuredly harmful, given that they were not benefiting from the approach and they were deprived of the opportunity to experience a treatment approach better suited to their needs.

I am hoping that this example in the specific context of minimal pairs intervention demonstrates that the concept of dosage can be very useful in speech therapy. We need much more research that establishes typical ranges of ‘dose’ for optimum outcomes for any given intervention procedure that we use. Then we need to track these dosages as we apply procedures in our interventions. It is important to remember that the dose is not the number of sessions or visits by the child or family to the SLP. Rather, the dose is number of learning opportunities experienced by the child. When the child is not learning and we know the child has experienced the optimum dose of practice trials, we can adjust our intervention procedures with greater confidence. We can also set evidence based goals for our clients and document objectively their progress with respect to these expectations. In addition to these benefits for individual clients, this kind of information will allow us to evaluate the efficacy of our service at the program level with an objectivity that is currently lacking. Imagine if a government or an insurance company suggested that they save money by reducing the dose of our medications below effective levels! We should not allow this solution to be proposed to reduce the cost of speech therapy services. The only way to protect ourselves and our clients is with more research and greater specificity about how our treatments work. We must know the right dosage.