Mobile Applications for Allergic Rhinitis

Objective: To study and review the currently available mobile applications relating to allergic rhinitis. Methods: The Apple and Google mobile app stores were queried with search terms relating to allergic rhinitis. Apps were assigned to categories and analyzed based on description and characteristics such as popularity, reviews, cost, platform, and physician involvement in development. Results: A total of 72 apps related to allergic rhinitis were identified. Fifty-four apps were unique, with 18 apps found on both operating systems. Forty (55.5%) apps were available in the Apple App store, and 32 (44.4%) apps were available in the Google Play app store. They were grouped into the following categories: patient education (18; 25%), journals (15; 20.8%), symptom tracking (14; 19.4%), clinical/private practice (13; 18.1%), pollen forecast (7; 9.7%), medical education (4; 5.6%), and other (1; 1.4%). The majority of apps were free of charge (67; 93.1%), with paid apps ranging from $1.47 to $4.99. Apps that were reviewed had an average rating of 3.9 out of 5. Physicians were involved in the development of 37 (51.4%) apps. Conclusions: The collection of mobile apps developed for allergic rhinitis includes those for both educational and clinical use. Mobile apps may have an increasing role in otolaryngic allergy and rhinology practices in the future. Thus, continued research is warranted to determine the best way to ensure the accuracy and quality of app content as well as the extent mobile apps can benefit allergic rhinitis patients.

Economic Valuation of a New Meteorological Information Service: Conjoint Analysis for a Pollen Forecast System

This study aims to investigate the public’s preferences for and quantitatively measure the economic value of a pollen forecast system, a new meteorological information service, in South Korea. To directly measure the economic value of the pollen forecast system and its attributes in terms of the public’s preferences, this study used conjoint analysis and a discrete choice model. In the conjoint survey, seven factors were considered as attributes of the pollen forecast system: the forecast area, forecast interval, information type, forecast period, delivery media, forecast accuracy, and price. Based on survey data from the six largest metropolitan areas in South Korea, the authors estimated people’s utility function by a rank-ordered logit model and calculated the relative importance (RI) and marginal willingness to pay (MWTP) for each attribute. People considered price, meaning the additional tax burden, to be the most important attribute, with a relative importance of 42.3%. In descending order of relative importance, price was followed by forecast accuracy, forecast interval, forecast area, forecast period, and information type; these attributes had MWTP values of 0.133, −0.017, 0.098, 0.059, and 0.011 USD month−1, respectively. The results of this study can serve as guidance of government investments in the pollen forecast system and provide an empirical basis for the application of conjoint analysis to economic valuation studies on a wider range of meteorological information services.