Are effect sizes in research papers useful in SLP practice?

Effect size blog figure 1Effect sizes are now required in addition to statistical significance reporting in scientific reports. As discussed in a previous blog, effect sizes are useful for research purposes because they can be aggregated across studies to draw conclusions (i.e., as, in a meta-analysis). However, they are also intended to be useful as an indication of the “practical consequences of the findings for daily life.” Therefore, Gierut, Morrisette, & Dickinson’s paper “Effect Size for Single-Subject Design in Phonological Treatment” was of considerable interest to me when it was published in 2015. They report the distribution of effect sizes for 135 multiple baseline studies using a pooled standard deviation for the baseline phase of the studies as the denominator and the mean of the treatment phase minus the mean of the baseline phase as the numerator in the equation to calculate the effect size statistic. In these studies, the mean and the variance of probe scores in the baseline phase is restricted to be very small by design, because the treatment targets and generalization probe targets must show close to stable 0% correct performance during the baseline phase. The consequence of this restriction is that the effect size number will be very large even when the raw amount of performance change is not so great. Therefore the figure above shows hypothetical data that yields exactly their average effect size of 3.66 (specifically, [8.57%-1.25%]/.02 = 3.66). This effect size is termed a medium effect size in their paper but I leave it to the reader to decide if a change of not quite 9% accuracy in speech sound production is an acceptable level of change. It may be because in these studies, a treatment effect is operationalized as probe scores (single word naming task) for all the phonemes that were absent from the child’s repertoire at intake. From the research point of view this paper provides very important information: it permits researchers to compare effect sizes and explore variables that account for between-case differences in effect sizes in those cases where the researchers have used a multiple baseline design and treatment intensities similar to those reported in this paper (5 to 19 one-hour sessions typically delivered 3 times per week).

The question I am asking myself is whether the distribution of effect sizes that is reported in this paper is helpful to clinicians who are concerned with the practical significance of these studies. I ask this because I am starting to see manuscripts reporting clinical case studies in which the data are used to claim “large treatment effects” for a single case (using Gierut et al’s standard of an effect size of 6.32 or greater). Indeed, in the clinical setting SLPs will be asked to consider whether their clients are making “enough” progress. For example, in Rvachew and Nowak (2001) we asked parents to rate their agreement with the statement “My child’s communication skills are improving as fast as can be expected.” (This question was on our standard patient satisfaction questionnaire so in fact, we asked every parent this question, not just the ones in this RCT). But the parent responses in the RCT showed that there were significant between group differences in response to this question that aligned with the dramatic differences in child response to the traditional versus complexity approach to target selection that was tested in that study (e.g., 34% vs. 17% of targets mastered in these groups respectively). It seems to me that when a parent asks themselves this question they have multiple frames of reference: not only do they consider the child’s communicative competence before and after the introduction of therapy, they consider whether their child would make more or less change with other hypothetical SLPs and other treatment approaches, given that parents actually have choices about these things. Therefore, an effect size that says effectively, the child made more progress with treatment compared to no treatment is not really answering the parent’s question. However, with a group design it is possible to calculate an effect size that reflects change relative to the average amount of change one might expect, given therapy. To my mind this kind of effect size comes closer to answering the questions about practical significance that a parent or employer might ask.

This still leaves us with the question of what kind of change to describe. It is unfortunate that there are few if any controlled studies that have reported functional measures. I can think of some examples of descriptive studies that reported functional measures however. First, Campbell (1999) reported that good functional outcomes were achieved when preschoolers with moderate and severe Speech Delay received twice-weekly therapy over a 90- to 120-day period (i.e., on average the children’s speech intelligibility improved from approximately 50% to 75% intelligible as reported by parents). Second, there are a number of studies reporting ASHA-NOMS (functional communication measures provided by treating SLPs) for children receiving speech and language therapy. However, Thomas-Stonell et al (2007) found that improvement on the ASHA-NOMS was not as sensitive as parental reports of “real life communication change” over a 3 to 6 month interval. Therefore, Thomas-Stonell and her colleagues developed the FOCUS to document parental reports of functional outcomes in a reliable and standardized manner.

Thomas-Stonell et al (2013) report changes in FOCUS scores for 97 preschool aged children who received an average of 9 hours of SLP service in Canada, comparing change during the waiting period (60 day interval) to change during the treatment period (90 day interval). FOCUS assessments demonstrated significantly more change during treatment (about 18 FOCUS points on average) than during the wait period (about 6 FOCUS points on average). Then they compared minimally important changes in PCC, the Children’s Speech Intelligibility Measure, and FOCUS scores for 28 preschool aged children. The FOCUS measure was significantly correlated with the speech accuracy and intelligibility measures but there was not perfect agreement among these measures. For example, 21/28 children obtained a minimally important change of at least 16 points on the FOCUS but 4 of those children did not show significant change on PCC/CSIM. In other words speech accuracy, speech intelligibility and functional improvements are related but not completely aligned; each provides independent information about change over time.

In controlled studies, some version of percent consonants correct is a very common treatment outcome that is used  to assess the efficacy of phonology therapy. Gierut et al (2015) focused specifically on change in those phonemes that are late developing and produced with very low accuracy, if not completely absent from the child’s repertoire at intake. This strikes me as a defensible measure of treatment outcome. Regardless of whether one chooses to treat a complex sound, an early developing sound, a medium-difficulty sound (or one of each as I demonstrated in a previous blog), presumably the SLP wants to have dramatic effects across the child’s phonological system. Evidence that the child is adding new sounds to the repertoire is a good indicator of that kind of change. Alternatively the SLP might count increases in correct use of all consonants that were potential treatment targets prior to the onset of treatment. Or, the SLP could count percent consonants correct for all the consonants because this measure is associated with intelligibility and takes into account the fact that there can be regressions in previously mastered sounds when phonological reorganization is occurring. The number of choices suggests that it would be valuable to have effect size data for a number of possible indicators of change. More to the point, Gierut et al’s single subject effect size implies that almost any change above “no change” is an acceptable level of change in a population that receives intervention because they are stalled without it. I am curious to know if this is a reasonable position to take. In my next blog post I will report effect sizes for these speech accuracy measures taken from my own studies going back to 2001. I will also discuss the clinical significance of the effect sizes that I will aggregate. I am going to calculate the effect size for paired mean differences along with the corresponding confidence intervals for groups of preschoolers treated in three different studies. I haven’t done the calculations yet, so, for those readers who are at all interested in this, you can hold your breath with me.

References

Campbell, T. F. (1999). Functional treatment outcomes in young children with motor speech disorders. In A. Caruso & E. A. Strand (Eds.), Clinical Management of Motor Speech Disorders in Children (pp. 385-395). New York: Thieme Medical Publishers, Inc.

Gierut, J. A., Morrisette, M. L., & Dickinson, S. L. (2015). Effect Size for Single-Subject Design in Phonological Treatment. Journal of Speech, Language, and Hearing Research, 58(5), 1464-1481. doi:10.1044/2015_JSLHR-S-14-0299

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 1-12. doi:10.3389/fpsyg.2013.00863

Thomas-Stonell, N., McConney-Ellis, S., Oddson, B., Robertson, B., & Rosenbaum, P. (2007). An evaluation of the responsiveness of the pre-kindergarten ASHA NOMS. Canadian Journal of Speech-Language Pathology and Audiology, 31(2), 74-82.

Thomas-Stonell, N., Oddson, B., Robertson, B., & Rosenbaum, P. (2013). Validation of the Focus on the Outcomes of Communication under Six outcome measure. Developmental Medicine and Child Neuroloogy, 55(6), 546-552. doi:10.1111/dmcn.12123

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.

 

 

 

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  1. How effective is phonology treatment? | Developmental Phonological Disorders

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