Pollution to prevention: digital decision support for air pollution and exercise counselling in general practice.

Clinical Snapshot

Key Findings

• P Value: Not applicable (descriptive study)

• Effect Size: Mean MARS score 3.6/5.0 (range 2.9-4.3)

• Primary Outcome: Digital tool quality assessment using MARS scale

• Nnt Or Sensitivity: Seven tools identified from digital landscape review

• Confidence Interval: Not reported

Clinical Application

Limited by lack of validated tools and clinical integration frameworks Highly relevant given similar air quality concerns in Australian cities; could inform TGA digital therapeutics pathway and RACGP preventive care guidelines General practice patients requiring exercise counselling, particularly those with cardiovascular or respiratory conditions

Abstract

BACKGROUND: Outdoor exercise supports physical, mental, and social wellbeing. However, exposure to air pollution during activity can increase cardiorespiratory risk. The Royal College of Physicians (A Breath of Fresh Air, 2025) urges clinicians to address environmental determinants of health, including air quality, during routine care, including annual checks. Patients increasingly use digital tools providing air-quality data and actionable behavioural recommendations, yet the quality, evidence base, and integration of these tools into clinical workflows remain unclear. AIM: To evaluate digital tools that help patients modify exercise behaviour based on air-pollution exposure to inform the development of a custom chatbot to support exercise counselling in primary care. METHOD: A scoping review of app libraries, grey literature, and peer-reviewed studies identified digital tools providing air-quality data with actionable exercise recommendations. Data extraction covered functionality, pollutants, validation, and quality using the Mobile App Rating Scale (MARS) and Behaviour Change Technique Taxonomy (BCTTv1). RESULTS: Seven tools were identified: IQAir, Plume Labs, BreezoMeter, EPA AirNow, PurpleAir, airTEXT, and AirTrack. MARS scores ranged from 2.9 to 4.3 (mean = 3.6/5.0), highest for functionality and aesthetics but lower for information accuracy and engagement. Behaviour change content was limited to general health information, and no tools demonstrated formal validation or clinical integration. CONCLUSION: Existing tools provide accessible air-quality data but lack individualised recommendations for exercise. Insights informed a custom chatbot embedding air-quality and exercise advice into GP cardiorespiratory annual reviews. Next steps include further development of the custom chatbot and pilot implementation in general practice to assess feasibility, clinician uptake, and patient outcomes.

References

1. 1.Velho, R., & Ward, P. (2026). Pollution to prevention: digital decision support for air pollution and exercise counselling in general practice. British Journal of General Practice. https://doi.org/10.3399/bjgp26X745557