In this study, we have developed, optimized, and applied a novel 3D in vitro cell culture platform composed of an interpenetrating network (IPN) that is both mechanically tunable and inherently bioactive. The IPN consists of a primary fibrillar collagen type-1 network reinforced by a secondary thiol-ene poly(ethylene glycol) (PEG) network. The IPNs are formed via a novel strategy in which cell-laden collagen gels are formed first, and soluble PEG monomers are added later and crosslinked via visible light. This approach ensures that the collagen gels contain a fibrillar architecture similar to the collagen architecture present in vivo. We applied our IPN platform to study the effect of mechanical confinement on cancer cell behavior and found that it inhibits malignant-like behavior.

Background There is no consensus on which risks to communicate to a prospective surgical patient during informed consent or how. Complicating the process, patient preferences may diverge from clinical assumptions and are often not considered for discussion. Such discrepancies can lead to confusion and resentment, raising the potential for legal action. To overcome these issues, we propose a visual consent tool that incorporates patient preferences and communicates personalized risks to patients using data visualization. We used this platform to identify key effective visual elements to communicate personalized surgical risks. Objective Our main focus is to understand how to best communicate personalized risks using data visualization. To contextualize patient responses to the main question, we examine how patients perceive risks before surgery (research question 1), how suitably the visual consent tool is able to present personalized surgical risks (research question 2), how well our visualizations convey those personalized surgical risks (research question 3), and how the visual consent tool could improve the informed consent process and how it can be used (research question 4). Methods We designed a visual consent tool to meet the objectives of our study. To calculate and list personalized surgical risks, we used the American College of Surgeons risk calculator. We created multiple visualization mock-ups using visual elements previously determined to be well-received for risk communication. Semistructured interviews were conducted with patients after surgery, and each of the mock-ups was presented and evaluated independently and in the context of our visual consent tool design. The interviews were transcribed, and thematic analysis was performed to identify major themes. We also applied a quantitative approach to the analysis to assess the prevalence of different perceptions of the visualizations presented in our tool. Results In total, 20 patients were interviewed, with a median age of 59 (range 29-87) years. Thematic analysis revealed factors that influenced the perception of risk (the surgical procedure, the cognitive capacity of the patient, and the timing of consent; research question 1); factors that influenced the perceived value of risk visualizations (preference for rare event communication, preference for risk visualization, and usefulness of comparison with the average; research question 3); and perceived usefulness and use cases of the visual consent tool (research questions 2 and 4). Most importantly, we found that patients preferred the visual consent tool to current text-based documents and had no unified preferences for risk visualization. Furthermore, our findings suggest that patient concerns were not often represented in existing risk calculators. Conclusions We identified key elements that influence effective visual risk communication in the perioperative setting and pointed out the limitations of the existing calculators in addressing patient concerns. Patient preference is highly variable and should influence choices regarding risk presentation and visualization.

Objective: Identify key elements of an effective visualization method for communicating personalized surgical risks to patients. Background: Currently, there is no consensus on which risks should be communicated during the informed consent process and how. Furthermore, patient preferences are often not considered during the consent process. These inefficiencies can lead to non-beneficial outcomes and raise the potential for legal implications. To address the limitations of the informed consent process, we propose a visual consent tool (VCT) that incorporates patient preferences and communicates personalized risks to patients using data visualization. Methods: To understand how patients perceive risk visualizations and their role in the informed consent discussion, we gathered feedback on visualizations by conducting semi-structured interviews during postoperative visits. Thematic analysis was performed to identify major themes. Iterative evaluation and consolidation of the major themes were performed with domain experts. Results: A total of 20 patients were interviewed for this study with a median age of 59 (sd = 14). The thematic analysis revealed factors that influence the perception of risk, of risk visualizations, and the usefulness of the proposed VCT. We found that patients preferred VCT over the current methods and had different preferences for risk visualization. Further, our findings suggest that surgical concerns of patients were not in line with existing risk calculators. Conclusion: We were able to identify key elements that influence effective risk communication in the perioperative setting. We found that patient preference is variable and should influence choices for risk presentation and visualization.