Digital Informed Consent/Assent in Clinical Trials Among Pregnant Women, Minors, and Adults: Multicountry Cross-Sectional Evaluation of Comprehension and Satisfaction
Bibliographic record
Abstract
Background: Informed consent (IC) is a cornerstone of ethical clinical research, yet comprehension gaps persist. The i-CONSENT guidelines aim to improve IC materials by enhancing clarity, accessibility, and tailoring them to the needs of diverse populations. This study evaluates the effectiveness of electronic IC (eIC) materials developed under these guidelines for 3 target populations-minors, pregnant women, and adults-across Spain, the United Kingdom, and Romania. Objective: The primary aim of this study is to assess participants' comprehension of and satisfaction with eIC materials tailored to their specific needs. The secondary objectives are to identify demographic predictors of comprehension, evaluate the cross-cultural applicability of materials, and explore format preferences. Methods: A cross-sectional study was conducted with 1757 participants (620 minors, 312 pregnant women, and 825 adults), who reviewed eIC materials through a digital platform offering layered web content, narrative videos, printable documents, and infographics. Materials were co-designed using participatory methods, including design thinking sessions with minors and pregnant women, and online surveys with adults. Comprehension was assessed using an adapted version of the Quality of the Informed Consent questionnaire. Objective comprehension (part A) was categorized as low (<70%), moderate (70%-80%), adequate (80%-90%), or high (≥90%). Subjective comprehension (part B) was measured using a 5-point Likert scale. Satisfaction was evaluated through Likert scales and usability questions, with scores ≥80% considered acceptable. Multivariable regression models were applied to identify predictors of comprehension. Results: Objective comprehension exceeded 80% across all groups: minors (mean 83.3, SD 13.5), pregnant women (mean 82.2, SD 11.0), and adults (mean 84.8, SD 10.8). Women/girls outperformed men/boys (β=+.16 to +.36). Generation X adults scored higher than millennials (β=+.26, P<.001), while prior trial participation was associated with lower comprehension scores (β=-.47 to -1.77). Among minors, compared with participants from Spain with no previous clinical trial experience, comprehension was significantly lower in Spain (P=.03), Romania (P<.001), and the United Kingdom (P<.001). Format preferences varied: 382 out of 620 (61.6%) minors and 152 out of 312 (48.7%) pregnant women preferred videos, whereas 452 out of 825 (54.8%) adults favored text (P<.001). Satisfaction rates surpassed 90% in all groups (minors, 604/620, 97.4%; pregnant women, 303/312, 97.1%; and adults, 804/825, 97.5%), with 777 out of 825 (94.2%) adults also indicating that the materials facilitated understanding. While translated materials maintained high efficacy across countries, comprehension scores in Romania were lower among participants with lower educational levels (β=-1.05, P=.001). Materials cocreated in Spain were effective across countries but yielded higher comprehension within the original target population. Conclusions: eIC materials developed following the i-CONSENT guidelines achieved high levels of comprehension and satisfaction across diverse populations, demonstrating scalability for multinational trials. Cocreation and multimodal design effectively addressed participant preferences; however, cultural adaptation remained crucial for optimizing outcomes. The negative impact of prior trial participation highlights the need for tailored engagement strategies for returning participants. Future research should explore regional disparities, evaluate interventions for overconfident returning participants, and validate these tools across broader cultural contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.079 | 0.146 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".