New study: Quantifying dosage in self-managed speech therapy

In recent years, speech therapy has evolved with the advent of digital health technologies, especially for patients living with neurological conditions like aphasia. Such tools enable self-managed, at-home speech therapy, offering patients greater flexibility and autonomy in their therapy programs and schedules. However, understanding the amount of therapy (“dosage”) that patients actually receive through such platforms has been challenging.

A new study by researchers at Boston University, published in the May 2024 issue of the American Journal of Speech-Language Pathology, explores this question using real-world data gathered from Constant Therapy’s digital speech, language and cognitive therapy program. Specifically, the study sought to assess whether a specific method for measuring speech therapy intensity previously applied in controlled clinical settings—known as the Cumulative Intervention Intensity (CII) framework—is also an applicable measurement of therapy dosage in self-directed, home-based contexts.

This BrainWire post summarizes the research’s key findings and discusses its implications for patients, caregivers, and clinicians.

What is the Cumulative Intervention Intensity (CII) framework for speech therapy?

The CII framework is designed to quantify the amount, or dosage, of speech therapy received by patients. It comprises several elements:

• Dose: The number of therapeutic inputs per session.
• Session frequency: How often sessions are conducted per week.
• Session duration: The length of each therapy session.
• Total intervention duration: The overall time span over which therapy is conducted.

This framework helps in calculating the total amount of therapy delivered, providing a composite score that reflects the cumulative intensity of the therapy regimen.

Study Design

Researchers analyzed anonymized data from 2,223 post-stroke survivors using the Constant Therapy app over a three-month period. They examined the four quantitative CII parameters—dose, session frequency, session duration, and total intervention duration. These parameters were analyzed for their interrelationships and their role in identifying user practice patterns through correlation analysis and k-means clustering, a statistical method.

Major Takeaways

1. Feasibility of CII in self-managed speech therapy: The study confirmed that components of CII can be calculated using data from a digital home health app like Constant Therapy, thereby providing a structured way to measure therapy dosage in a self-managed setting.
2. Interrelationships between dosage parameters: Although related, the various CII parameters offered unique insights into therapy practices. Session frequency, in particular, provided distinct information from other parameters like session duration and total intervention. This suggests that the regularity of therapy sessions can significantly impact patient adherence and recovery outcomes, reflecting a patient’s commitment to integrating therapy into daily routines.
3. Practice patterns: Users could be grouped into three categories based on their practice habits:
   • Minimal practice: Infrequent, low-dosage settings may indicate barriers such as motivation or understanding.
   • Moderate, intensive practice: Sporadic, high-dosage sessions could suggest preferences for focused, intense therapy bouts.
   • Maximal, frequent practice: Regular, moderate-dosage sessions likely represent optimal engagement, suggesting good habit formation and the potential for best outcomes.
4. Implications for therapy management: Understanding these patterns can help tailor patient therapy programs more effectively, potentially improving outcomes by optimizing the frequency and intensity of interventions and augmenting patient education about the benefits of consistent engagement.

Conclusion

This study offers a pioneering look into how self-managed, digital speech therapy can be quantified using the CII framework. These findings advocate for a nuanced approach to dosage measurement that might revolutionize patient outcomes by enabling more personalized therapy regimens. This adaptability is crucial not only for enhancing the efficacy of interventions but also for ensuring sustained engagement and maximizing recovery in post-stroke rehabilitation.

By harnessing real-world data from Constant Therapy’s app, it also underscores the significant potential of technology to transform traditional therapy models, offering a deeper, data-driven insight into patient engagement and therapy effectiveness.

At Constant Therapy, we are excited to be on the frontline of that transformation and are honored to see our evidence-based, AI-powered program put to work in cutting-edge research that continues to push the bounds of the neurorehabilitation field forward.

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