Evidence map›Paper›PMID 40367513›Full record

SynthesisJournal of medical Internet research2025

Context-Contingent Privacy Concerns and Exploration of the Privacy Paradox in the Age of AI, Augmented Reality, Big Data, and the Internet of Things: Systematic Review.

Christian Herriger, Omar Merlo, Andreas B Eisingerich, Annisa Rizkia Arigayota

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Christian HerrigerImperial Business School, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0009-0004-0780-9133
Omar MerloImperial Business School, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-4421-3679
Andreas B EisingerichImperial Business School, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-5531-4662
Annisa Rizkia ArigayotaImperial Business School, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0009-0004-4394-7170

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite extensive research into technology users' privacy concerns, a critical gap remains in understanding why individuals adopt different standards for data protection across contexts. The rise of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR), and big data has created rapidly evolving and complex privacy landscapes. However, privacy is often treated as a static construct, failing to reflect the fluid, context-dependent nature of user concerns. This oversimplification has led to fragmented research, inconsistent findings, and limited capacity to address the nuanced challenges posed by these technologies. Understanding these dynamics is especially crucial in fields such as digital health and informatics, where sensitive data and user trust are central to adoption and ethical innovation.

objectiveThis study synthesized existing research on privacy behaviors in emerging technologies, focusing on IoT, AI, AR, and big data. Its primary objectives were to identify the psychological antecedents, outcomes, and theoretical frameworks explaining privacy behavior, and to assess whether insights from traditional online privacy literature, such as e-commerce and social networking, apply to these advanced technologies. It also advocates a context-dependent approach to understanding privacy.

methodsA systematic review of 179 studies synthesized psychological antecedents, outcomes, and theoretical frameworks related to privacy behaviors in emerging technologies. Following established guidelines and using leading research databases such as ScienceDirect (Elsevier), SAGE, and EBSCO, studies were screened for relevance to privacy behaviors, focus on emerging technologies, and empirical grounding. Methodological details were analyzed to assess the applicability of traditional privacy findings from e-commerce and social networking to today's advanced technologies.

resultsThe systematic review revealed key gaps in the privacy literature on emerging technologies, such as IoT, AI, AR, and big data. Contextual factors, such as data sensitivity, recipient transparency, and transmission principles, were often overlooked, despite their critical role in shaping privacy concerns and behaviors. The findings also showed that theories developed for traditional technologies often fall short in addressing the complexities of modern contexts. By synthesizing psychological antecedents, behavioral outcomes, and theoretical frameworks, this study underscores the need for a context-contingent approach to privacy research.

conclusionsThis study advances understanding of user privacy by emphasizing the critical role of context in data sharing, particularly amid ubiquitous and emerging health technologies. The findings challenge static views of privacy and highlight the need for tailored frameworks that reflect dynamic, context-dependent behaviors. Practical implications include guiding health care providers, policy makers, and technology developers toward context-sensitive strategies that build trust, enhance data protection, and support ethical digital health innovation.

trial registrationPROSPERO CRD420251037954; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251037954.

Indexed as

Artificial IntelligenceAugmented RealityBig DataInternet of ThingsPrivacyHumansartificial intelligencecontextual integrityInternet of Thingsprivacy concernsprivacy paradoxsystematic literature review

Identifiers

PMID40367513
PMCPMC12120372

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.