In a number of sectors, a rapid approach to detect those who are susceptible to skin issues would be valuable. Certain subgroups, such as persons with atopic dermatitis, may be more prone to skin irritation and more likely to file product-related complaints than the average customer. For this study, researchers wanted to create a quick, questionnaire-based algorithm for predicting whether or not people with skin problems have atopic dermatitis. A 9-item questionnaire on self-perceived skin sensitivity and product categories reportedly associated with skin reactions was given to two groups of patients from a dermatology clinic: one with clinically diagnosed, active atopic dermatitis (n=25) and another with dermatologic complaints unrelated to atopic dermatitis (n=25). Questionnaire responses were compared to patients’ clinical diagnoses to determine the smallest number of questions required to accurately predict the patients’ initial diagnosis. In a group of dermatology clinic patients, replies to a series of three focused questions on self-perceived skin sensitivity, preference for hypoallergenic products, and reactions to or avoidance of -hydroxy acids were found to be highly predictive of atopic dermatitis.
The notion of a prediction algorithm might be used in postmarketing monitoring programs to quickly analyze the probable status of customers who make frequent or persistent product-related complaints. This notion will be refined and validated using samples from the general population as well as consumers who report skin issues related to personal items.
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