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Meta-therapy in conversation training therapy (Martineau et al., 2025)

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posted on 2025-07-03, 22:17 authored by Sarah Martineau, Jackie Gartner-Schmidt, Leah B. Helou
<p dir="ltr"><b>Purpose: </b>Meta-therapy (MT) is a clinical entity that plays a pivotal role in the success of voice therapy. This descriptive study is the first empirical research to describe and quantify the use of MT in comparison to other treatment modalities during conversation training therapy (CTT).</p><p dir="ltr"><b>Method: </b>Twenty-four prerecorded CTT sessions featuring six voice-specialized speech-language pathologists (SLPs) were converted into audio files and transcribed into text files. Trained annotators (experienced and novice voice-specialized SLPs) identified the use of MT and four other treatment modalities (direct treatment, education and indirect treatment, and counseling) during the therapy sessions. Descriptive statistics and intra- and inter-annotator agreements (Cohen’s kappa) were generated.</p><p dir="ltr"><b>Results: </b>MT was used systematically throughout the course of CTT, both as a stand-alone therapeutic approach and in conjunction with other treatment modalities. When blended with other treatment modalities, MT accounted, on average, for 31% of all clinical dialogues within the course of treatment. Intra-annotation reliability was generally high. However, inter-annotator reliability was notably lower and did not differ between novice and experienced SLPs, not only for MT but also for the other four treatment modalities.</p><p dir="ltr"><b>Conclusions: </b>This study underscores the multifaceted nature of MT and supports the notion that it is a core element of voice therapy. We propose that MT could be formally taught to future SLPs alongside other clinical components (e.g., indirect treatment, direct treatment, and counseling). This study also highlights the need for standardization and operationalization of all key components of voice therapy.</p><p dir="ltr"><b>Supplemental Material S1. </b>Overview of the definitions provided for the annotation in this study.</p><p dir="ltr"><b>Supplemental Material S2. </b>Time distribution for SLP 1.</p><p dir="ltr"><b>Supplemental Material S3. </b>Time distribution for SLP 3.</p><p dir="ltr"><b>Supplemental Material S4. </b>Time distribution for SLP 4.</p><p dir="ltr"><b>Supplemental Material S5. </b>Time distribution for SLP 5.</p><p dir="ltr"><b>Supplemental Material S6. </b>Time distribution for SLP 6.</p><p dir="ltr"><b>Supplemental Material S7. </b>Pairwise comparisons with Cohen’s kappa coefficient for Inter-annotator agreement for Direct treatment among all annotators, for every dyad and every session.</p><p dir="ltr"><b>Supplemental Material S8. </b>Pairwise comparisons with Cohen’s kappa coefficient for Inter-annotator agreement for Education and Indirect treatment among all annotators, for every dyad and every session.</p><p dir="ltr"><b>Supplemental Material S9. </b>Pairwise comparisons with Cohen’s kappa coefficient for Inter-annotator agreement for Counseling among all annotators, for every dyad and every session.</p><p dir="ltr"><b>Supplemental Material S10.</b> Mean time (with range) spent with the task of annotating per session.</p><p dir="ltr"><b>Supplemental Material S11. </b>Mean self-rated attention on a 0 to 10 scale with the task of annotating per session with standard deviations.</p><p dir="ltr"><b>Supplemental Material S12. </b>Mean self-rated enjoyment with the task of annotating per session.</p><p dir="ltr"><b>Supplemental Material S13. </b>Mean self-rated confidence on a 0 to 10 scale with the task of annotating per session and treatment modalities with standard deviations.</p><p dir="ltr">Martineau, S., Gartner-Schmidt, J., & Helou, L. B. (2025). Quantification of meta-therapy in conversation training therapy. <i>American Journal of Speech-Language Pathology, </i><i>34</i>(5), 2649–2665. <a href="https://doi.org/10.1044/2025_AJSLP-24-00308" target="_blank">https://doi.org/10.1044/2025_AJSLP-24-00308</a></p>

Funding

This study was supported by Fonds de recherche du Québec – Santé Grant 2022-2023-BF7-315926 (awarded to Sarah Martineau; https://doi.org/10.69777/315926).

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