Exploring Cough Reduction Through Digital Content – Case Studies from CoughPro's Cough Management Features

Summary

Case studies on digital behavioral interventions for chronic cough management inside CoughPro, demonstrating promising reductions in cough frequency through AI-powered monitoring and science-based suppression techniques.

This paper evaluates the potential of CoughPro's cough management features. Coughpro is a welness cough monitoring app that integrates digital behavioral interventions to manage chronic cough. The paper uses three case studies, to highlight interesting trends in cough reduction among users engaging with the app’s Cough Management features. The findings suggest digital therapeutics (DTx) targeting Chronic Cough could serve as a viable alternative or complement to traditional chronic cough treatments, necessitating further rigorous studies.

Background and Clinical Context

Chronic cough affects 5-10% of adults, significantly impairing quality of life through physical and psychosocial effects. Conventional treatments focus on addressing underlying causes such as asthma or gastroesophageal reflux disease (GERD), but treatment efficacy is inconsistent. Behavioral Cough Suppression Therapy (BCST) has demonstrated success in reducing cough frequency but remains largely inaccessible. CoughPro aims to bridge this gap through a digital, science-based approach.

CoughPro and Its Cough Management Features

CoughPro is a smartphone-based wellness app that provides continuous cough monitoring using Hyfe’s AI-powered detection models. The Cough Management module introduces a structured intervention based on BCST, with three key components:

  1. Education – Explains cough hypersensitivity and the science behind behavioral suppression techniques.
  2. Techniques – Guides users through specific methods for reducing the urge to cough.
  3. Triggers – Helps users identify and manage cough-inducing stimuli.

Methodology

  • Data Collection: Anonymized data from users who engaged with the Cough Management feature and met inclusion criteria (e.g., 18+ hours of cough tracking).
  • Metrics: Hourly cough rate (CpH), cough bursts, and pre-/post-intervention comparisons.
  • Limitations: Small sample size, potential confounding factors (e.g., concurrent treatments), and variability in adherence to cough monitoring.

Key Findings from Case Studies - Three users with different cough profiles demonstrated intriguing cough reduction following engagement with Cough Management.

Discussion and Implications - The findings support the hypothesis that digital BCST interventions, delivered via an accessible mobile platform, can significantly impact chronic cough outcomes. Digital therapeutics could complement existing treatments by improving adherence, providing real-time feedback, and addressing accessibility challenges in traditional therapy. However, larger, controlled studies are required to validate these preliminary observations.

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