PRISM: Evaluating a Rule-Based, Scenario-Driven Social Media Privacy Education Program for Young Autistic Adults

• URL: http://arxiv.org/abs/2604.07531v1
• Date: Wed, 08 Apr 2026 19:13:59 GMT
• Title: PRISM: Evaluating a Rule-Based, Scenario-Driven Social Media Privacy Education Program for Young Autistic Adults
• Abstract summary: Twenty-nine autistic students with substantial (level 2) support needs participated in a 14-week social media privacy literacy class.<n>Our course focused on empowering them by providing more nuanced guidance on safe privacy practices through the use of scenario-based formats and contextual, rule-based scenarios.<n>Using pre- and post-knowledge assessments for each of our 6 course topics, our intervention led to a statistically significant increase in their making safer social media privacy decisions.
• Score: 15.263018609771464
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Young autistic adults may garner benefits through social media but also disproportionately experience privacy harms. Prior research found that these harms often stem from perceiving the affordances of social media differently than the general population, leading to unintentional risky behaviors and interactions with others. While educational interventions have been shown to increase social media privacy literacy for the general population, research has yet to focus on effective educational interventions for autistic young adults. We address this gap by developing and deploying Privacy Rules for Inclusive Social Media (PRISM), a classroom-based educational intervention tailored to the unique risks and neurodevelopmental differences of this population. Twenty-nine autistic students with substantial (level 2) support needs participated in a 14-week social media privacy literacy class. During these classes, participants often communicated their existing rule-based "all or nothing" approaches to privacy management (such as completely disengaging from social media to avoid privacy issues). Our course focused on empowering them by providing more nuanced guidance on safe privacy practices through the use of scenario-based formats and contextual, rule-based scenarios. Using pre- and post-knowledge assessments for each of our 6 course topics, our intervention led to a statistically significant increase in their making safer social media privacy decisions. We conclude with recommendations for how privacy educators and technology designers can leverage neuro-affirming educational interventions to increase privacy literacy for autistic social media users.

Related papers

• Profiling for Pennies: Unveiling the Privacy Iceberg of LLM Agents [52.02752011119451]
  We investigate privacy perception in the real world through the lens of human awareness.<n>We propose the PrivacyIceberg, which categorizes real-world human privacy risks into three tiers.
  arXiv  Detail & Related papers  (2026-05-07T13:21:44Z)
• The Psychological Impacts of Algorithmic and AI-Driven Social Media on Teenagers: A Call to Action [0.0]
  This study investigates the meta-issues surrounding social media. Our investigation reveals a paradoxical outcome: rather than fostering closer relationships and improving social lives, the algorithms and structures that underlie social media contribute to a profound psychological impact on individuals. This phenomenon is particularly pronounced among teenagers, who are disproportionately affected by curated online personas, peer pressure to present a perfect digital image, and the constant bombardment of notifications and updates that characterize their social media experience.
  arXiv  Detail & Related papers  (2024-08-19T18:49:12Z)
• Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory [43.12744258781724]
  We formulate the privacy issue as a reasoning problem rather than simple pattern matching.<n>We develop the first comprehensive checklist that covers social identities, private attributes, and existing privacy regulations.
  arXiv  Detail & Related papers  (2024-08-19T14:48:04Z)
• NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human [56.46355425175232]
  We suggest sanitizing sensitive text using two common strategies used by humans.<n>We curate the first corpus, coined NAP2, through both crowdsourcing and the use of large language models.<n>Compared to the prior works on anonymization, the human-inspired approaches result in more natural rewrites.
  arXiv  Detail & Related papers  (2024-06-06T05:07:44Z)
• Secure Aggregation is Not Private Against Membership Inference Attacks [66.59892736942953]
  We investigate the privacy implications of SecAgg in federated learning. We show that SecAgg offers weak privacy against membership inference attacks even in a single training round. Our findings underscore the imperative for additional privacy-enhancing mechanisms, such as noise injection.
  arXiv  Detail & Related papers  (2024-03-26T15:07:58Z)
• Sex differences in attitudes towards online privacy and anonymity among Israeli students with different technical backgrounds [0.6445605125467572]
  Our aim was to comparatively model men and women's online privacy attitudes. Various factors related to the user's online privacy and anonymity were considered. Users' tendency to engage in privacy paradox behaviour was not higher among men despite their higher level of technological online privacy literacy compared to women.
  arXiv  Detail & Related papers  (2023-08-07T12:36:37Z)
• User Perception of Privacy with Ubiquitous Devices [5.33024001730262]
  This study aims to explore and discover various concerns related to perception of privacy in this era of ubiquitous technologies. Key themes like attitude towards privacy in public and private spaces, privacy awareness, consent seeking, dilemmas/confusions related to various technologies, impact of attitude and beliefs on individuals actions regarding how to protect oneself from invasion of privacy in both public and private spaces.
  arXiv  Detail & Related papers  (2021-07-23T05:01:44Z)
• Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data [74.60507696087966]
  Mental health conditions remain underdiagnosed even in countries with common access to advanced medical care. One promising data source to help monitor human behavior is daily smartphone usage. We study behavioral markers of daily mood using a recent dataset of mobile behaviors from adolescent populations at high risk of suicidal behaviors.
  arXiv  Detail & Related papers  (2021-06-24T17:46:03Z)
• Applications of Differential Privacy in Social Network Analysis: A Survey [60.696428840516724]
  Differential privacy is effective in sharing information and preserving privacy with a strong guarantee. Social network analysis has been extensively adopted in many applications, opening a new arena for the application of differential privacy.
  arXiv  Detail & Related papers  (2020-10-06T19:06:03Z)
• Usable, Acceptable, Appropriable: Towards Practicable Privacy [2.0305676256390934]
  This paper explores the privacy needs of marginalized and vulnerable populations. We introduce computers and the Internet to a group of sex-trafficking survivors in Nepal. We highlight a few socio-political factors that have influenced the design space around digital privacy.
  arXiv  Detail & Related papers  (2020-04-15T21:39:33Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.