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      An Experimental Study of Recommendation Algorithms for Tailored Health Communication

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          Abstract

          Recommendation algorithms are widely used in online cultural markets to provide personalized suggestions for products like books and movies. At the heart of the commercial success of recommendation algorithms is their ability to make an accurate prediction of a target person’s preferences for previously unseen items. Can these algorithms also be used to predict which health messages an individual will evaluate favorably, and thereby provide effective tailored communication to the person? Although there is evidence that message tailoring enhances persuasion, little research has examined the effectiveness of recommendation algorithms for tailored health interventions aimed at promoting behavior change. We developed a message tailoring algorithm to select smoking-related public service announcements (PSAs) for smokers, and experimentally test its effectiveness in predicting a target smoker’s evaluations of PSAs and encouraging smoking cessation. The tailoring algorithm was constructed using multiple levels of data on smokers’ PSA rating history, individual differences, content features of the PSAs, and other smokers’ PSA ratings. We conducted a longitudinal online experiment to examine its efficacy in comparison to two non-tailored methods: “best in show” (choosing messages most preferred by other smokers) and “off the shelf” (random selection from eligible ads). The results showed that the tailoring algorithm produced more accurate predictions of smokers’ message evaluations than the simple-average method used for the “best in show” approach. Smokers who viewed PSAs recommended by the tailoring algorithm were more likely than those receiving a random set to evaluate the PSAs favorably and quit smoking. There was no significant difference between the “best in show” and “off the shelf” methods in message assessment and quitting behavior.

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          Most cited references41

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              The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire.

              We examine and refine the Fagerström Tolerance Questionnaire (FTQ: Fagerström, 1978). The relation between each FTQ item and biochemical measures of heaviness of smoking was examined in 254 smokers. We found that the nicotine rating item and the inhalation item were unrelated to any of our biochemical measures and these two items were primary contributors to psychometric deficiencies in the FTQ. We also found that a revised scoring of time to the first cigarette of the day (TTF) and number of cigarettes smoked per day (CPD) improved the scale. We present a revision of the FTQ: the Fagerström Test for Nicotine Dependence (FTND).
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                Author and article information

                Journal
                CCR
                Computational Communication Research
                Amsterdam University Press
                2665-9085
                2665-9085
                01 October 2019
                : 1
                : 1
                : 103-129
                Article
                CCR2019.1.005.SUKK
                10.5117/CCR2019.1.005.SUKK
                17646162-e950-42ec-89a0-3bf2725256ab
                © 2019 Amsterdam University Press
                History
                Page count
                Pages: 27
                Categories
                Articles

                health communication,Recommendation algorithms,message tailoring

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