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Journal Article
Research Support, Non-U.S. Gov't
Quantifying Dosage in Self-Managed Speech-Language Therapy: Exploring Components of Cumulative Intervention Intensity in a Real-World Mobile Health Data Set.
PURPOSE: Cumulative Intervention Intensity (CII) is a proposed framework for conceptualizing and calculating dose that has been used to quantify intensity of speech-language therapy (SLT) in highly controlled laboratory studies and clinical trials. However, it is unknown whether CII can be applied to characterize the practice patterns of patients undertaking at-home, self-managed SLT. The current study leverages real-world mobile health data to investigate the applicability of CII parameters to self-managed SLT, including the interrelationships between individual CII parameters and their utility for identifying naturally occurring subgroups of patient users.
METHOD: Anonymized data from 2,223 poststroke survivors who used the Constant Therapy application were analyzed. Four quantitative CII parameters-dose, session frequency, session duration, and total intervention duration-were calculated per user over a 3-month analysis period using raw session-level data. We conducted correlation analyses at the level of the individual and group to examine the degree of relatedness between each of the CII parameters. CII parameter measures were additionally used as inputs to a k-mean clustering analysis to identify practice pattern subgroups.
RESULTS: Results demonstrate the feasibility of calculating components of CII based on available usage statistics from a commercial app for self-managed SLT. Specifically, results suggest that, although CII parameters are related, session frequency offers complementary and nonoverlapping information (cf. dose, session duration, total intervention duration) about dosage. Clustering results show that practice patterns can be broadly differentiated according to the (a) amount and (b) frequency of practice.
CONCLUSIONS: The calculation of CII may provide both users and clinicians with a fuller picture of at-home, self-managed practice habits than looking at any one dosage component alone. The study represents a first step toward more comprehensive and theoretically grounded dose reporting for self-managed SLT.
SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25511191.
METHOD: Anonymized data from 2,223 poststroke survivors who used the Constant Therapy application were analyzed. Four quantitative CII parameters-dose, session frequency, session duration, and total intervention duration-were calculated per user over a 3-month analysis period using raw session-level data. We conducted correlation analyses at the level of the individual and group to examine the degree of relatedness between each of the CII parameters. CII parameter measures were additionally used as inputs to a k-mean clustering analysis to identify practice pattern subgroups.
RESULTS: Results demonstrate the feasibility of calculating components of CII based on available usage statistics from a commercial app for self-managed SLT. Specifically, results suggest that, although CII parameters are related, session frequency offers complementary and nonoverlapping information (cf. dose, session duration, total intervention duration) about dosage. Clustering results show that practice patterns can be broadly differentiated according to the (a) amount and (b) frequency of practice.
CONCLUSIONS: The calculation of CII may provide both users and clinicians with a fuller picture of at-home, self-managed practice habits than looking at any one dosage component alone. The study represents a first step toward more comprehensive and theoretically grounded dose reporting for self-managed SLT.
SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25511191.
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