Automated informed consent
Research article
Adam John Andreotta, Björn Lundgren
Big Data & Society, 18 October 2024
Open access
Abstract
Online privacy policies or terms and conditions ideally provide users with information about how their personal data are being used. The reality is that very few users read them: they are long, often hard to understand, and ubiquitous. The average internet user cannot realistically read and understand all aspects that apply to them and thus give informed consent to the companies who use their personal data. In this article, we provide a basic overview of a solution to the problem. We suggest that software could allow users to delegate the consent process and consent could thus be automated. The article investigates the practical feasibility of this idea. After suggesting that it is feasible, we develop some normative issues that we believe should be addressed before automated consent is implemented.

Editor’s Note: We are concerned that the core argument being made in this article challenges the integrity of the informed consent process. 

Informed consent in the age of smart technologies
Jaana Leikas, Arja Halkoaho, Marinka Lanne
Finnish Journal of eHealth and eWelfare, 14 October 2024
Abstract
     Technology is increasingly being brought into the home care of older people. Digitalization is seen as an enabler for efficient and resource-saving operations. In the use of technology, informed consent is considered an ethical practice and part of a responsible home care service system. The aim of this article is to describe the problem of informed consent in situations where emerging technologies, such as artificial intelligence (AI) and mass data, are used as part of welfare services and home care for older people. The article discusses principles and ways to better integrate informed consent as an ethical practice into a responsible home care service system.

A qualitative study was carried out to gather the views of experts in the field of elderly care and ethics. A content analysis of a semi-structured focus group was used to explore perceptions of the changing nature of informed consent. According to our findings, the informed consent model requires updating. The key is to embrace the idea that consent is a living process designed to respect people’s autonomous choices and protect them from risk. If the nature of the use of the data collected from individuals changes significantly in the future, the consent should also be updated to reflect this change. This aspect is important because new technologies will change the nature of the collection and use of the data. Mass data collection combines multiple databases so that the resulting data can be used even far from the original purpose or context in which it was collected. Therefore, consent should always be tailored to the context, allowing sufficient time for the person seeking and giving consent to clarify the content of the consent. This process highlights the importance of understanding the agency of the consent giver.

Using Large Language Models to Create Patient Centered Consent Forms
Beattie, S. Neufeld, D.X. Yang, C. Chukwuma, N.B. Desai, M. Dohopolski, S.B. Jiang
International Journal of Radiation Oncology, Biology, Physics, 1 October 2024
Abstract
Purpose/Objective(s)
Understanding informed consent forms, which outline the risks, costs, and procedures of clinical trials, presents a significant challenge for patients due to their complex language and length. Recognizing that such complexity can impede patient comprehension and decision-making, this study proposes the use of Large Language Models (LLMs) to distill these forms into concise, easy-to-understand cover pages. We hypothesize that we can significantly improve the readability of these forms using LLMs.
Materials/Methods
Five approved institutional clinical trial consent forms were assessed for their readability using SMOG and the Flesch-Kincaid Ease of Reading score using Python libraries. The documents were segmented and catalogued in a vector database to facilitate similarity searches. OpenAI’s GPT-4 API was prompted to extract information about costs, payments, contact information, eligibility criteria, treatments, duration, and requirements based on relevant information retrieved from the vector database. Furthermore, each prompt included instructions to respond at a 7th to 8th-grade reading level. The answers were collected, and their readability evaluated using the aforementioned metrics. Finally, the SMOG and Flesch-Kincaid readability scores were compared using a Wilcoxon signed-rank test.
Results
The original informed consent forms exhibited an average SMOG score of 16.74 (± 0.86), corresponding to a graduate reading level, and an average Flesch-Kincaid score of 12.93 (± 0.70), corresponding to an undergraduate reading level. Conversely, the LLM-generated information sheets exhibited an average SMOG score of 11.25 (± 0.50), corresponding to a high school reading level, and an average Flesch-Kincaid score of 8.15 (± 0.68), corresponding to an 8-9th grade reading level, demonstrating a significant reduction in reading level (p<0.05 for both SMOG and Flesh-Kincaid scores). Some LLM-generated information sheets were successful in adhering to a 7th to 8th-grade reading level, as denoted by a Flesch-Kincaid score < 8.
Conclusion
Our approach successfully simplified clinical trial consent forms using LLMs, reducing reading levels and making information more accessible. This approach could significantly enhance the transparency and comprehensibility of the clinical trial consent process, fostering a more patient-centric approach. Feedback from patients on LLM-generated information sheets could provide invaluable insights into the practicality and usefulness of this approach.

Multi-Center Pilot Study to Assess Provider Experience with an Artificial Intelligence Multimedia Informed Consent Platform
Usman Latif, Timothy Deer, Sean Li
Neuromodulation: Technology at the Neural Interface, October 2024
Introduction
Informed consent is a keystone of medical care, involving a thorough discussion of the procedure, risks and benefits involved, and reasonable expectations for patients. 24% of malpractice suits in the field of spine surgery are attributable to insufficient informed consent. Numerous studies indicate that informed consent is frequently inadequate. Multimedia aids have been shown to enhance patient comprehension and satisfaction. This study assessed experience at multiple centers with a platform that delivers multimedia videos and utilizes artificial intelligence to ensure patients view the entire video while maintaining attention before signing a digital consent. A permanent videographic record of the patient viewing the video is created for the purpose of reducing malpractice exposure.

Editor’s Note: After assessing the observations and arguments made in this paper, we are reaching out to the corresponding authors for clarification.