“I” Am Willing to Disclose, but “We” are Unwilling: The Impact of Self-Construal on Individuals’ Willingness to Disclose

Abstract

Purpose: In the big data era, many institutions (ie, hospitals) and firms use various methods to encourage people to disclose more personal information to gain competitive advantages in many businesses, such as healthcare and the Internet of Things (IoT) devices. Discussions on antecedents of individuals' willingness to reveal private data from individual differences perspective are limited. Drawing on information boundary theory, we examine how selfconstrual prompts a different regulatory focus (promotion focus versus prevention focus), thus, affects individuals' willingness to disclose private data. Methods: A mixed-method approach was used to examine our hypothesis. Study 1 (N = 93, participants in China) manipulated self-construal in lab experiments and examined participants' actual disclosure behavior in the emerging IoT context of connected cars. Study 2 (an online survey, N = 200, participants in US) measured chronic self-construal in another disclosure context (healthcare app), replicating the preliminary effect and examined the mediating effect of the regulatory focus. Study 3 (an online experiment, N = 284, participants in US) tested the moderating effect of message framing. Results: Study 1 showed that participants primed an independent self-construal were more willing to share private information, whether it is real driving data or private identity information. Study 2 showed that independent (interdependent) self-construal individuals tend to have promotion focus (prevention focus), thus leading to higher (lower) willingness to disclose personal health information. Study 3 demonstrated that independent (interdependent) self-construal individuals are more willing to share information when presented with gain-framing (loss-framing) information. Conclusion: Independent (interdependent) self-construal positively (negatively) affects individuals' willingness to disclose and these effects will be mediated by regulatory focus and moderated by message farming. Our study provides a theoretical paradigm that is new to the willingness to disclose literature, and offers an effective, actionable strategy on how institutions and firms can facilitate individuals' personal information disclosure.

Designing mindfulness information for interaction in social media: The role of information framing, health risk perception and lay theories of health

“…Previous researchers have found that higher selfefficacy are related to greater participation in health-promoting behaviors, and higher exercise intensity and frequency (Luszczynska et al, 2011;Dong et al, 2018). Furthermore, in an experimental study, self-efficacy was positively correlated with incremental health theory which was positively correlated with participation in health-related behavior, but negatively correlated with entity health theory which was negatively correlated with participation in health-related behavior (Zhang C. et al, 2021;Zhang N. et al, 2021). Van't Riet et al (2010) examined the influence of self-efficacy on skin self-examination on the effects of different framed skin-cancer detection information.…”

“…Research on the information effects has shown that there is a positive correlation between perceived risk and willingness to share information with others. People with a higher level of perceived risk are more likely to engage in health protection behaviors ( Zhang C. et al, 2021 ; Zhang N. et al, 2021 ), and there is a significant correlation between risk perception and self-reported preventive health behaviors ( Dryhurst et al, 2020 ). In addition, researchers also found that the severity of perceived risk was associated with recommended behavioral changes ( Rubin et al, 2009 ).…”

“…Previous research demonstrated that those tended to consider health is malleable(incremental)were more likely to engage in health behaviors than those tended to consider health fixed (entity; Bunda and Busseri, 2019 ). Recent studies have also shown that lay theories of health can predict the possibility of people participating in health protection behaviors mediated by variables that people consider future consequences ( Zhang C. et al, 2021 ; Zhang N. et al, 2021 ).…”

Ethical Considerations on Some Issues of Medical Artificial Intelligence Applications

“…Personal information and identifiability Zhang, et al define personal information as "any information relating to an identified or identifiable person" [18]. That is, when a person is identifiable, any information related to that person is personal information, and confidentiality is the basis for the empowerment of personal information.…”

“…If the above-mentioned scheme for data collection, preservation, extraction, and use can be established, the secondary use of AI data can be achieved for the benefit of human health while ensuring patient privacy and data security. With the development of AI technology, the implementation of deidentification is not static, and the boundary between absolute anonymity and identifiable information is becoming increasingly blurred [18]. It is indeed difficult to achieve zero risk of identification as well as absolute and permanent anonymity.…”