Internet opt-in and opt-out

Lai, Yee-Lin; Hui, Kai Lung

doi:10.1145/1125170.1125230

Cited by 38 publications

(6 citation statements)

References 24 publications

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“…Results of the papers show that the use of traditional auto completion tools, usually found in web forms, could cause significantly more information being disclosed [75], while restrictive default privacy settings helped users to share less information on online social networks [76]. Also, the use of an opt-in frame, comparing to an opt-out frame, for the provision of consent proved to be a more effective strategy towards protecting users' privacy [77] while pre-selected options within a choice frame may increase user participation in online activities such as sign up [78].…”

Section: Nudging With Defaultsmentioning

confidence: 99%

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

et al. 2021

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Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how nudges can confound one another.

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Section: Nudging With Defaultsmentioning

confidence: 99%

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

et al. 2021

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“…According to the German Genetic Diagnostics Act, a person has the “right not to know” and dismiss information about any aspect of their genetic condition. Thus, iKNOW takes a cautious approach to providing information and releases information for each topic separately and only after obtaining consent (via a mouse click) [ 17 , 28 ]. That is, during every step of the counseling process, it is the physicians together with the counselees who decide whether or not a particular piece of information should be discussed.…”

Section: Design Principles Supporting Personalized Counseling With Di...mentioning

confidence: 99%

Paradigmatic Approach to Support Personalized Counseling With Digital Health (iKNOW)

Speiser¹,

Heibges²,

Besch³

et al. 2023

JMIR Form Res

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iKNOW is the first evidence-based digital tool to support personalized counseling for women in Germany with a hereditary cancer risk. The counseling tool is designed for carriers of pathogenic gBRCA (germline breast cancer gene) variants that increase the lifetime risk of breast and ovarian cancer. Carriers of pathogenic variants are confronted with complex, individualized risk information, and physicians must be able to convey this information in a comprehensible way to enable preference-sensitive health decisions. In this paper, we elaborate on the clinical, regulatory, and practical premises of personalized counseling in Germany. By operationalizing these premises, we formulate 5 design principles that, we suggest, are specific enough to develop a digital tool (eg, iKNOW), yet wide-ranging enough to inform the development of counseling tools for personalized medicine more generally: (1) digital counseling tools should implement the current standard of care (eg, based on guidelines); (2) digital counseling tools should help to both standardize and personalize the counseling process (eg, by enabling the preference-sensitive selection of counseling contents from a common information base); (3) digital counseling tools should make complex information easy to access both cognitively (eg, by using evidenced-based risk communication formats) and technically (eg, by means of responsive design for various devices); (4) digital counseling tools should respect the counselee’s data privacy rights (eg, through strict pseudonymization and opt-in consent); and (5) digital counseling tools should be systematically and iteratively evaluated with the users in mind (eg, using formative prototype testing to ensure a user-centric design and a summative multicenter, randomized controlled trial). On the basis of these paradigmatic design principles, we hope that iKNOW can serve as a blueprint for the development of more digital innovations to support personalized counseling approaches in cancer medicine.

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“…Knijnenburg, Kobsa, & Jin, 2013b), and • What the default is and how one asks (i.e., "default" and "framing" effects, cf. Knijnenburg & Kobsa, 2014;Lai & Hui, 2006). Some privacy researchers therefore hypothesize that people predominantly use shortcuts for making privacy decisions (Acquisti & Grossklags, 2008;Adjerid, Acquisti, Brandimarte, & Loewenstein, 2013;Cho, Lee, & Chung, 2010;LaRose & Rifon, 2006;Lowry et al, 2012).…”

Section: Elaboration Likelihood Model For Privacy Decision Makingmentioning

confidence: 99%

The effect of personalization provider characteristics on privacy attitudes and behaviors: An Elaboration Likelihood Model approach

Kobsa

Cho

Knijnenburg

2016

Asso for Info Science & Tech

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Many computer users today value personalization but perceive it in conflict with their desire for privacy. They therefore tend not to disclose data that would be useful for personalization. We investigate how characteristics of the personalization provider influence users' attitudes towards personalization and their resulting disclosure behavior. We propose an integrative model that links these characteristics via privacy attitudes to actual disclosure behavior. Using the Elaboration Likelihood Model, we discuss in what way the influence of the manipulated provider characteristics is different for users engaging in different levels of elaboration (represented by the user characteristics of privacy concerns and self‐efficacy). We find particularly that (a) reputation management is effective when users predominantly use the peripheral route (i.e., a low level of elaboration), but much less so when they predominantly use the central route (i.e., a high level of elaboration); (b) client‐side personalization has a positive impact when users use either route; and (c) personalization in the cloud does not work well in either route. Managers and designers can use our results to instill more favorable privacy attitudes and increase disclosure, using different techniques that depend on each user's levels of privacy concerns and privacy self‐efficacy.

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Internet opt-in and opt-out

Cited by 38 publications

References 24 publications

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis

Paradigmatic Approach to Support Personalized Counseling With Digital Health (iKNOW)

The effect of personalization provider characteristics on privacy attitudes and behaviors: An Elaboration Likelihood Model approach

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