Prioritizing Attention over Privacy: Analysis of Face Image Posting Behavior in Online Direct-to-Consumer Genetic Testing Forum (Preprint)

BACKGROUND As direct-to-consumer genetic testing (DTC-GT) services have grown in popularity, the public has increasingly relied upon online forums to discuss and share their test results. Initially, users did so under a pseudonym, but more recently, they have included face images when discussing DTC-GT results. When these images truthfully represent a user, they reveal the identity of the corresponding individual. Various studies have shown that sharing images in social media tends to elicit more replies. However, users who do this clearly forgo their privacy. OBJECTIVE This study aimed to investigate the face image sharing behavior of DTC-GT users in an online environment and determine if there exists the association between face image sharing and the attention received from others. METHODS This study focused on r/23andme, a subreddit dedicated to discussing DTC-GT results and their implications. We applied natural language processing to infer the themes associated with posts that included a face image. We applied a regression analysis to learn the association between the attention that a post received, in terms of the number of comments and karma scores (defined as the number of upvotes minus the number of downvotes), and whether the post contains a face image. RESULTS We collected over 15,000 posts from the r/23andme subreddit published between 2012 and 2020. Face image posting began in late 2019 and grew rapidly, with over 800 individuals’ revealing their faces by early 2020. The topics in posts including a face were primarily about sharing or discussing ancestry composition, and sharing family reunion photos with relatives discovered via DTC-GT. On average, posts including a face received 60% (5/8) more comments than other posts, and these posts had karma scores 2.4 times higher than other posts. CONCLUSIONS DTC-GT consumers in the r/23andme subreddit are increasingly posting face images and testing reports on social platforms. The association between face image posting and a greater level of attention suggests that people are forgoing their privacy in exchange for attention from others. To mitigate the risk of face image posting, platforms, or at least subreddit organizers, should inform users about the consequence of such behavior for identity disclosure.

“You Could Tell I Said the Wrong Things”: Constructions of Sexual Identity Among Older Gay Men in Healthcare Settings

Older gay men commonly conceal their sexual identity in healthcare settings due to past experiences and expectations of encountering stigma and discrimination in these contexts. Although insights on how older gay men construct their sexual identity in healthcare may help contextualize this phenomenon, this question remains under-explored. Accordingly, we present the findings of a secondary grounded theory analysis of individual interview data, which we originally collected to examine the healthcare experiences of 27 gay men ages 50 and over, to explore constructions of sexual identity among the group. Our findings broadly reveal that older gay men’s varying exposure to intersecting systems of oppression, together with their perceptions of different healthcare settings, may be critical in shaping their constructions of sexual identity in these contexts. Our research supports the need for healthcare policies and practices that address stigma and discrimination as salient barriers to sexual identity disclosure among older gay men.

The Role of Minority Stress and Social Resources in the Healthcare Utilization of Aging LGBT Adults

Research suggests that minority stress can influence the healthcare utilization of aging LGBT adults, and that social resources can buffer the effect of stress on healthcare utilization. Using data from Aging with Pride: National Health, Aging, and Sexuality/Gender Study (N = 2,560), multiple logistic regression assessed the associations between minority stress (i.e., internalized stigma and LGBT identity disclosure) and healthcare utilization (i.e., health screenings, emergency room use, routine checkups, and regular provider). We also examined the moderating effect of social resources, including social network size, social support, and LGBT community belonging, in these associations. Internalized stigma was negatively associated with having a routine checkup in the previous year (OR = 0.82, p = .038). Disclosure was positively associated with having a health screening within the past 3 years (OR = 1.52, p = .000) and having a regular provider (OR = 1.33, p = .021). Further, we found that social support moderated the association between disclosure and health screenings (OR = 1.52, p < .001); thus, having higher levels of social support and disclosure in tandem increased the likelihood of getting a health screening in the last three years. Health and human service professionals should provide information about internalized stigma and LGBT identity disclosure to educate their clients about the ways in which these minority stressors can impact their healthcare experiences. Providers should assess the social support of their aging LGBT clients and inform them about the added benefit that social support can have in their healthcare experiences.

Latent Classes of Bidirectional Face-to-Face and Cyber Intimate Partner Violence Among Lesbian, Gay, and Bisexual Emerging Adults: The Role of Minority Stressors

The rates of intimate partner violence have been found to be higher among lesbian, gay, and bisexual (LGB) individuals when compared with heterosexual populations. However, lesser is known about the impact of specific minority stressors experienced by LGB populations on their face-to-face intimate partner violence (IPV) and cyber IPV experiences. Using a three-step latent class approach, the present study investigated (i) the latent classes of self-reported types of face-to-face IPV and cyber IPV perpetration and victimization and (ii) their associations with LGB distal and proximal minority stressors (i.e., vicarious trauma, discrimination, family rejection, and LGB-identity disclosure). Participants were 288 LGB emerging adults in the age range of 18–29 years (bisexual: n = 168, gay: n = 72, and lesbian: n = 48). Findings showed the presence of four latent classes, namely, face-to-face IPV ( n = 32; 37.5% gay, 18.8% lesbian, and 43.8% bisexual individuals), cyber IPV ( n = 66; 33.3% gay, 12.1% lesbian, and 54.5% bisexual individuals), psychological and stalking cyber IPV ( n = 89; 15.7% gay, 15.7% lesbian, and 68.5% bisexual individuals), and low IPV ( n = 101; 23.8% gay, 19.8% lesbian, and 56.4% bisexual individuals). Furthermore, multinomial logistic regressions indicated that greater exposure to the minority stressors such as exposure to heterosexism, namely, discrimination and harassment, rejection from one’s family of origin, and exposure to vicarious trauma, as well as a lower degree of LGB-identity disclosure, largely predicted latent classes with greater probabilities of IPV exposure, namely, cyber IPV, face-to-face IPV classes, and psychological and stalking cyber IPV. Findings suggest the importance of addressing the role of minority stressors in IPV interventions and the creation of competent LGB-related services and training modules for clinicians.

An Extended Mondrian Algorithm – XMondrian to Protect Identity Disclosure

In recent days, Privacy Preserving Data Publishing (PPDP) is considered as vital research area due to rapid increasing rate of data being published in the Internet day by day. Many Organizations often need to publish their data in internet for research and analysis purpose, but there is no guarantee that those data would be used only for ethical purposes. Hence data anonymization comes into picture and play a vital role in preventing identity disclosure, also it restricts the amount of data that can be seen or used by the external users. It is an extensively used PPDP technique among data encryption, data anonymization and data perturbation methods. Mondrian is considered as one such data anonymization technique that has outperformed compare to many anonymization algorithms, because of its fast and scalable nature. However, the algorithm insists to encode the categorical values into numerical values and decode it, to generalize the data. To overcome this problem, a new extended version of Mondrian algorithm is proposed, and it is called XMondrian algorithm. The proposed algorithm can handle both numerical and categorical attributes without encoding or decoding the categorical values.The effectiveness of the proposed algorithm has been analysed through experimental study and observed that the proposed XMondrian algorithm outshine the existing Mondrian algorithm in terms of anonymization time and Cavg. Cavg is one of the metric used to quantify the utility of data.

Utilizing the Four Tenets of Osteopathic Medicine as an intersectional framework for approaching sexual orientation and gender identity disclosure as a provider

The Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and other (LGBTQI+) community continues to experience health inequity and unmet needs. This manuscript examines the application of the Four Tenets of Osteopathic Medicine (FTOM) during a patient’s self-disclosure of their sexual orientation and/or gender identity to the provider, also known as coming out. Tenet One discusses the interplay between intersectionality and coming out. Tenet Two elucidates how coming out moves toward a balance of homeostasis and self-healing. Tenet Three examines how structure and function can be understood on a personal level and how society influences coming out. Tenet Four explains the resources available to facilitate the previously forementioned changes. By applying the Four Tenets, the provider may more readily understand what “coming out” means on personal and social levels and what implications they may have on their patients’ health.

Quasi-Identifier Recognition Algorithm for Privacy Preservation of Cloud Data Based on Risk Reidentification

Cloud computing plays an essential role as a source for outsourcing data to perform mining operations or other data processing, especially for data owners who do not have sufficient resources or experience to execute data mining techniques. However, the privacy of outsourced data is a serious concern. Most data owners are using anonymization-based techniques to prevent identity and attribute disclosures to avoid privacy leakage before outsourced data for mining over the cloud. In addition, data collection and dissemination in a resource-limited network such as sensor cloud require efficient methods to reduce privacy leakage. The main issue that caused identity disclosure is quasi-identifier (QID) linking. But most researchers of anonymization methods ignore the identification of proper QIDs. This reduces the validity of the used anonymization methods and may thus lead to a failure of the anonymity process. This paper introduces a new quasi-identifier recognition algorithm that reduces identity disclosure which resulted from QID linking. The proposed algorithm is comprised of two main stages: (1) attribute classification (or QID recognition) and (2) QID dimension identification. The algorithm works based on the reidentification of risk rate for all attributes and the dimension of QIDs where it determines the proper QIDs and their suitable dimensions. The proposed algorithm was tested on a real dataset. The results demonstrated that the proposed algorithm significantly reduces privacy leakage and maintains the data utility compared to recent related algorithms.

Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey

With opportunities brought by Internet of Things (IoT), it is quite a challenge to assure privacy preservation when a huge number of resource-constrained distributed devices is involved. Blockchain has become popular for its benefits, including decentralization, persistence, immutability, auditability and consensus. With the implementation of blockchain in IoT, the benefits provided by blockchain can be derived in order to make IoT more efficient and maintain trust. In this paper, we discuss some applications of IoT in different fields and privacy-related issues faced by IoT in resource-constrained devices. We discuss some applications of blockchain in vast majority of areas, and the opportunities it brings to resolve IoT privacy limitations. We, then, survey different researches based on the implementation of blockchain in IoT. The goal of this paper is to survey recent researches based on the implementation of blockchain in IoT for privacy preservation. After analyzing the recent solutions, we see that the blockchain is an optimal way for preventing identity disclosure, monitoring, and providing tracking in IoT.