The Effects of Risk Disclosure in Direct-to-Consumer Prescription Drug Advertising (DTCA): Prominence, DTCA Regulatory Knowledge, and Perceived Attention

Fair balance of benefit and risk information in consumer prescription drug advertising (DTCA) has received much research attention. In this regard, it has been well-documented that varying levels of risk disclosure prominence have disproportional effects on consumer response to the DTC ad. However, little research has examined how the prominence effects can be maximized or minimized depending on consumers’ varying levels of knowledge of the FDA’s regulatory role for DTCA. In a similar vein, rare research has been conducted to investigate how such regulatory knowledge directly affects consumers’ risk disclosure coping strategies. Drawing on consumer information processing perspectives, this research employs an experimental approach to examine one manipulated categorical variable, one measured continuous variable, and their interactive effects on consumer response to the ad, while controlling for potential covariates. Specifically, two levels of risk disclosure prominence are manipulated (high vs. low) and coded as a dummy variable, and DTCA regulatory knowledge is measured as a continuous variable. Further, based on the persuasion knowledge model (PKM) framework, DTCA regulatory knowledge is tested as a moderator of the prominence effects. Consumer memory such as unaided-recall and aided-recognition of the health risks of the medicine presented in the ad as well as self-reported perceived attention to risk disclosure are addressed as criterion variables. The major findings are summarized as follows: (1) both higher DTCA regulatory knowledge and higher prominence enhanced perceived attention to risk disclosure; (2) both higher DTCA regulatory knowledge and higher prominence enhanced consumer recognition of risk information; (3) DTCA regulatory knowledge moderated the prominence effects on perceived attention to risk disclosure; (4) the main DTCA regulatory knowledge effects and the main prominence effects on consumer recall and recognition were mediated through perceived attention to risk disclosure; (5) However, the moderated mediation effect analyses revealed that the effects of prominence on recall and recognition were mediated through perceived attention among low DTCA regulatory knowledge consumers, whereas the mediating effects were minimal among high DTCA regulatory knowledge consumers. The overall findings support the current study’s conceptual framework. The theoretical, managerial, and consumer education/public health implications of this research are discussed

The Effects of Message Quantification: The Modearing Role of Numeracy

Although the numerical information effects has been reported in persuasive contexts, little research has investigated how numeric information in the drug efficacy appeals may affect consumers\u27 evaluation of DTC advertising. Based on an experiment, the current study revealed that: (a) consumers reported more positive perceived message effectiveness of and attitude toward advertising toward numeric DTC advertising; (b) when consumers were lowly numerate, the persuasive effects of numeric information was stronger. When consumers were highly numerate, however, the persuasive effects of numeric information was significantly reduced; and (c) perceived message effectiveness was found to be a valid indicator of actual DTC advertising effectiveness, by mediating between the numeric information effects and attitude toward DTC advertising. Theoretical and practical/regulatory implications of DTC advertising were discussed

The Influences of Perceived Environmental Responsibilities on Green Purchasing Intentions

The current study examined the influences of perceived environmental responsibilities of the three types of important social agents (individuals, companies, and governments) on consumers’ green purchasing intentions. Drawing on the environmental consumerism and purchase decision making literature, consumers’ perceptions of the aforementioned social agents’ roles in environment protection were hypothesized to influence their purchase intentions for green products. In addition, the current study attempted to investigate the different prediction patterns of such factors for two different purchase intention measures (e.g., general purchase intention and “willingness to pay more” for green products) to capture the nuance between the different measurement scales, which has been ignored in the green purchasing literature. An analysis of the nationally representative 2009 Experian Simmons National Consumer Study revealed that perceived personal norm of the environment was the strongest predictor of general purchase intention for green products, whereas perceived role of governmental regulation on green issues was the strongest predictor of “willingness to pay more.” Theoretical, managerial, and regulatory implications are discussed

Spiral of Silence in an Algorithm-Driven Social Media Content Environment: Conceptual Framework and Research Propositions

The aim of this conceptual study is to explore the major tenets of the spiral of silence theory (i.e., fear of isolation, willingness to speak out, quasi-statistical sense) within social media environments, where users are predominantly shown content that aligns with their views and interests. In this environment of algorithmic-suggested content, the researchers offer several propositions as to how the spiral of silence tenets operate relative to the perceived anonymity, tie strengths, and the postings suggested by programmed algorithms used by social media platforms. New research directions on spiral of silence theory, social media communication, and opinion polarization are also discussed. Finally, implications for researchers, policymakers, and social media practitioners are addressed

DTC Advertising and Perceived Importance of Illness: Two-sided Message and The moderating Role of DTCA Skepticism

To better understand consumers\u27 coping mechanisms of DTC advertising and to address socially important health issues, the current study examined whether perceived importance of sleep disorders is influenced by DTC advertising. Two-sided message order and DTCA skepticism were hypothesized as predictors of the perceived importance. The results showed that there is interaction between order effects and DTCA skepticism. Theoretical, practical, and regulatory implications are discussed

Communication Strategies in Direct-to-Consumer Prescription Drug Advertisements

Little research has incorporated a theoretical framework for the analysis of message and creative strategies used in DTCA to date. The purpose of the current study is to extend the previous literature by providing a more complete list of DTCA message and/or creativity strategies based on Taylor’s message strategy wheel. The results show that DTCA has been used to promote drugs for such life-threatening conditions as asthma, acid reflux, Alzheimer’s disease, depression, and arthritis. The most common inducement was the offer of consumer support information. In general, magazine DTC ads from 2006 to 2010 were likely to take both informational and transformational approaches. The comprehensive list of message and creative strategies found in this study would indicate what strategies might be available for existing marketers or new entrants into the DTCA category. However, the use of emotional appeals in DTCA suggests a public policy concern. The theoretical, public policy, and managerial implications are discussed

The Effects of Statistical Information in Pharmaceutical Product Advertising

In the contexts of prescription drug (DTC) advertising, statistical information has been frequently used. However, little is known about how the statistical information affects consumer attitude toward the advertisement and perceived importance of an advertised illness. Based on an experiment, the present study explored the mechanism of consumers\u27 DTC advertising information processing using structural equation modeling (SEM) approach. The findings revealed that: (a) the use of statistical information in DTC advertising positively related to perceived message effectiveness; (b) perceived message effectiveness positively related to attitude toward the advertisement and perceived importance of an advertised illness; and (c) message framing (gain versus loss) moderated the statistical information effects on consumers\u27 perceptions. Theoretical and practical implications of DTC advertising were discussed

A Radiomics Approach on Chest CT Distinguishes Primary Lung Cancer from Solitary Lung Metastasis in Colorectal Cancer Patients

Purpose: This study utilized a radiomics approach combined with a machine learning algorithm to distinguish primary lung cancer (LC) from solitary lung metastasis (LM) in colorectal cancer (CRC) patients with a solitary pulmonary nodule (SPN). Materials and Methods: In a retrospective study, 239 patients who underwent chest computerized tomography (CT) at three different institutions between 2011 and 2019 and were diagnosed as primary LC or solitary LM were included. The data from the first institution were divided into training and internal testing datasets. The data from the second and third institutions were used as an external testing dataset. Radiomic features were extracted from the intra and perinodular regions of interest (ROI). After a feature selection process, Support vector machine (SVM) was used to train models for classifying between LC and LM. The performances of the SVM classifiers were evaluated with both the internal and external testing datasets. The performances of the model were compared to those of two radiologists who reviewed the CT images of the testing datasets for the binary prediction of LC versus LM. Results: The SVM classifier trained with the radiomic features from the intranodular ROI and achieved the sensitivity/specificity of 0.545/0.828 in the internal test dataset, and 0.833/0.964 in the external test dataset, respectively. The SVM classifier trained with the combined radiomic features from the intra- and perinodular ROIs achieved the sensitivity/specificity of 0.545/0.966 in the internal test dataset, and 0.833/1.000 in the external test data set, respectively. Two radiologists demonstrated the sensitivity/specificity of 0.545/0.966 and 0.636/0.828 in the internal test dataset, and 0.917/0.929 and 0.833/0.929 in the external test dataset, which were comparable to the performance of the model trained with the combined radiomics features. Conclusion: Our results suggested that the machine learning classifiers trained using radiomics features of SPN in CRC patients can be used to distinguish the primary LC and the solitary LM with a similar level of performance to radiologists