Communicating With Diverse Patients About Participating in a Biobank: A Randomized Multisite Study Comparing Electronic and Face-to-Face Informed Consent Processes

Simon, Christian; Wang, Kai; Shinkunas, Laura; Stein, Daniel T.; Meißner, Paul; Smith, Maureen E.; Pentz, Rebecca D.; Klein, David

doi:10.1177/15562646211038819

Cited by 8 publications

(11 citation statements)

References 84 publications

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“…Different methods were used across studies to assess comprehension, some of which were more robust than others in their approaches. Overall, 10 studies included established instruments to assess comprehension, and their methodological validity was thus categorized as “high” (score=+++) [ 13 - 15 , 25 , 27 , 28 , 35 , 39 , 41 , 47 ]. The instruments used included the Brief Informed Consent Evaluation Protocol [ 15 , 52 ], Digitized Informed Consent Comprehension Questionnaire [ 14 , 51 ], MacArthur Competence Assessment Tool for Clinical Research [ 25 , 28 , 54 ], Quality of Informed Consent [ 13 , 35 , 39 , 41 , 47 , 50 ], and University of California San Diego Brief Assessment of Capacity to Consent [ 25 , 27 , 28 , 53 ].…”

Section: Resultsmentioning

confidence: 99%

“…Overall, 60% (6/10) of the “high” validity studies reported significantly better understanding with eConsent than paper-based ICFs for at least some of the concepts assessed using established instruments, with no statistical tests in favor of the paper process [ 14 , 15 , 25 , 28 , 35 , 39 ]. The remaining 4 (40%) of the 10 studies reported no significant difference in comprehension between eConsent and a paper-based consent process [ 13 , 27 , 41 , 47 ], with 1 study reporting statistically nonsignificant better comprehension using eConsent [ 27 ]. However, confidence in understanding was significantly lower with eConsent than with paper-based ICFs in 1 study that observed no difference in overall understanding [ 41 ].…”

Section: Resultsmentioning

confidence: 99%

“…The remaining 4 (40%) of the 10 studies reported no significant difference in comprehension between eConsent and a paper-based consent process [ 13 , 27 , 41 , 47 ], with 1 study reporting statistically nonsignificant better comprehension using eConsent [ 27 ]. However, confidence in understanding was significantly lower with eConsent than with paper-based ICFs in 1 study that observed no difference in overall understanding [ 41 ].…”

Section: Resultsmentioning

confidence: 99%

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Comparative Effectiveness of eConsent: Systematic Review

Cohen¹,

Byrom²,

Becher³

et al. 2023

J Med Internet Res

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Background Providing informed consent means agreeing to participate in a clinical trial and having understood what is involved. Flawed informed consent processes, including missing dates and signatures, are common regulatory audit findings. Electronic consent (eConsent) uses digital technologies to enable the consenting process. It aims to improve participant comprehension and engagement with study information and to address data quality concerns. Objective This systematic literature review aimed to assess the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, and study enrollment and retention rates, as well as the effects of eConsent on the time patients took to perform the consenting process (“cycle time”) and on-site workload in comparison with traditional paper-based consenting. Methods The systematic review was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Ovid Embase and Ovid MEDLINE were systematically searched for publications reporting original, comparative data on the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, enrollment and retention rates, cycle time, and site workload. The methodological validity of the studies that compared outcomes for comprehension, acceptability, and usability across paper consent and eConsent was assessed. Study methodologies were categorized as having “high” validity if comprehensive assessments were performed using established instruments. Results Overall, 37 publications describing 35 studies (13,281 participants) were included. All studies comparing eConsenting and paper-based consenting for comprehension (20/35, 57% of the studies; 10 with “high” validity), acceptability (8/35, 23% of the studies; 1 with “high” validity), and usability (5/35, 14% of the studies; 1 with “high” validity) reported significantly better results with eConsent, better results but without significance testing, or no significant differences in overall results. None of the studies reported better results with paper than with eConsent. Among the “high” validity studies, 6 studies on comprehension reported significantly better understanding of at least some concepts, the study on acceptability reported statistically significant higher satisfaction scores, and the study on usability reported statistically significant higher usability scores with eConsent than with paper (P<.05 for all). Cycle times were increased with eConsent, potentially reflecting greater patient engagement with the content. Data on enrollment and retention were limited. Comparative data from site staff and other study researchers indicated the potential for reduced workload and lower administrative burden with eConsent. Conclusions This systematic review showed that compared with patients using paper-based consenting, patients using eConsent had a better understanding of the clinical trial information, showed greater engagement with content, and rated the consenting process as more acceptable and usable. eConsent solutions thus have the potential to enhance understanding, acceptability, and usability of the consenting process while inherently being able to address data quality concerns, including those related to flawed consenting processes.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Comparative Effectiveness of eConsent: Systematic Review

Cohen¹,

Byrom²,

Becher³

et al. 2023

J Med Internet Res

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show abstract

“…For an electronic consent form to be useful and equitable, the information it provides needs to be readable, accurate, and complete . Despite national recommendations that they be written for a sixth-grade reading level, studies have shown that informed consent documents are overly complex .…”

Section: Introductionmentioning

confidence: 99%

“…13 For an electronic consent form to be useful and equitable, the information it provides needs to be readable, accurate, and complete. 14 Despite national recommendations that they be written for a sixth-grade reading level, studies have shown that informed consent documents are overly complex. [15][16][17][18][19][20][21] A possible solution to this problem is to leverage artificial intelligence, including generative large language model (LLM)−based chatbots that have been trained to respond to human-generated inquiries.…”

Section: Introductionmentioning

confidence: 99%

Large Language Model−Based Chatbot vs Surgeon-Generated Informed Consent Documentation for Common Procedures

Decker,

Trang,

Ramirez

et al. 2023

JAMA Netw Open

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ImportanceInformed consent is a critical component of patient care before invasive procedures, yet it is frequently inadequate. Electronic consent forms have the potential to facilitate patient comprehension if they provide information that is readable, accurate, and complete; it is not known if large language model (LLM)-based chatbots may improve informed consent documentation by generating accurate and complete information that is easily understood by patients.ObjectiveTo compare the readability, accuracy, and completeness of LLM-based chatbot- vs surgeon-generated information on the risks, benefits, and alternatives (RBAs) of common surgical procedures.Design, Setting, and ParticipantsThis cross-sectional study compared randomly selected surgeon-generated RBAs used in signed electronic consent forms at an academic referral center in San Francisco with LLM-based chatbot-generated (ChatGPT-3.5, OpenAI) RBAs for 6 surgical procedures (colectomy, coronary artery bypass graft, laparoscopic cholecystectomy, inguinal hernia repair, knee arthroplasty, and spinal fusion).Main Outcomes and MeasuresReadability was measured using previously validated scales (Flesh-Kincaid grade level, Gunning Fog index, the Simple Measure of Gobbledygook, and the Coleman-Liau index). Scores range from 0 to greater than 20 to indicate the years of education required to understand a text. Accuracy and completeness were assessed using a rubric developed with recommendations from LeapFrog, the Joint Commission, and the American College of Surgeons. Both composite and RBA subgroup scores were compared.ResultsThe total sample consisted of 36 RBAs, with 1 RBA generated by the LLM-based chatbot and 5 RBAs generated by a surgeon for each of the 6 surgical procedures. The mean (SD) readability score for the LLM-based chatbot RBAs was 12.9 (2.0) vs 15.7 (4.0) for surgeon-generated RBAs (P = .10). The mean (SD) composite completeness and accuracy score was lower for surgeons’ RBAs at 1.6 (0.5) than for LLM-based chatbot RBAs at 2.2 (0.4) (P &lt; .001). The LLM-based chatbot scores were higher than the surgeon-generated scores for descriptions of the benefits of surgery (2.3 [0.7] vs 1.4 [0.7]; P &lt; .001) and alternatives to surgery (2.7 [0.5] vs 1.4 [0.7]; P &lt; .001). There was no significant difference in chatbot vs surgeon RBA scores for risks of surgery (1.7 [0.5] vs 1.7 [0.4]; P = .38).Conclusions and RelevanceThe findings of this cross-sectional study suggest that despite not being perfect, LLM-based chatbots have the potential to enhance informed consent documentation. If an LLM were embedded in electronic health records in a manner compliant with the Health Insurance Portability and Accountability Act, it could be used to provide personalized risk information while easing documentation burden for physicians.

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“If It’s Ethical During a Pandemic…”: Lessons from COVID-19 for Post-Pandemic Biobanking

Goldenberg

Cadigan

2021

The American Journal of Bioethics

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Communicating With Diverse Patients About Participating in a Biobank: A Randomized Multisite Study Comparing Electronic and Face-to-Face Informed Consent Processes

Cited by 8 publications

References 84 publications

Comparative Effectiveness of eConsent: Systematic Review

Comparative Effectiveness of eConsent: Systematic Review

Large Language Model−Based Chatbot vs Surgeon-Generated Informed Consent Documentation for Common Procedures

“If It’s Ethical During a Pandemic…”: Lessons from COVID-19 for Post-Pandemic Biobanking

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