Measuring Informed Consent Comprehension: Strategies, Tools, and Outcomes for Clinical Research

Abstract

This article provides a comprehensive guide for researchers and drug development professionals on measuring informed consent comprehension. It explores the critical gap between consent documentation and true participant understanding, synthesizing current evidence on assessment methodologies. The scope covers foundational concepts of comprehension deficits, validated measurement tools, strategies for optimizing understanding across diverse populations, and comparative analysis of traditional versus innovative consent processes. By integrating empirical studies and systematic reviews, this resource aims to equip clinical trial teams with practical approaches to enhance ethical consent practices and ensure genuine participant comprehension in clinical research.

The Comprehension Gap in Informed Consent: Establishing the Need for Measurement

Documenting the Scale of Understanding Deficits in Clinical Trial Participants

Informed consent is a foundational ethical requirement in clinical research, yet significant gaps in participant comprehension persist, potentially undermining the validity of the consent process and participant welfare. Measuring these understanding deficits is crucial for improving participant engagement, ethical standards, and data quality in clinical trials. Recent advances in assessment methodologies, from standardized psychometric instruments to digital consent platforms, provide researchers with sophisticated tools to quantify and address comprehension gaps. This guide objectively compares the current methodologies for measuring understanding deficits, providing drug development professionals with the experimental data and protocols needed to select appropriate assessment strategies for their clinical trials.

Comparing Comprehension Assessment Instruments

The selection of an appropriate assessment instrument is critical for accurately measuring understanding deficits. The following comparison details the properties of key tools and methodologies documented in recent research.

Table 1: Comparison of Clinical Trial Comprehension Assessment Instruments

Instrument/Method	Primary Construct Measured	Population Validated On	Reliability (Cronbach's α)	Key Strengths	Implementation Context
Clinical Research Involvement Scales (CRIS) [1]	Attitudes, beliefs, and willingness to participate in clinical research	Diverse populations (N=919) including African Americans and women	0.734 – 0.918 (across subscales)	High reliability across diverse populations; measures multiple theoretical domains	Pre-recruitment assessment; community engagement research
Quality of Informed Consent (QuIC) Questionnaire [2]	Objective and subjective comprehension of informed consent materials	Minors, pregnant women, and adults across three countries (N=1,757)	Adapted and validated for each target population	Assesses both actual and perceived understanding; cross-culturally validated	Direct evaluation of consent comprehension post-consent process
Digital Informed Consent (eIC) Assessment [2]	Comprehension of trial information presented via digital platforms	Minors (n=620), pregnant women (n=312), adults (n=825) across Spain, UK, Romania	Not specified (uses objective scoring metrics)	Multi-format presentation (video, layered text, infographics); accommodates preferences	Electronic consent platforms; decentralized clinical trials

Experimental Protocols for Key Assessment Methodologies

Protocol 1: CRIS Instrument Development and Validation

The Clinical Research Involvement Scales (CRIS) were developed through a rigorous methodology to assess factors influencing clinical trial participation decisions [1].

Scale Development Workflow:

Methodological Details:

• Domain Identification: Researchers identified eight theoretical domains influencing participation decisions, including attitudes, subjective norms, behavioral beliefs, outcome evaluations, normative beliefs, motivation to comply, organizational involvement, and personal relevance of volunteerism [1].
• Item Generation: Initial items were developed based on previous quantitative and qualitative research, literature review, and HIV clinical and community experience. A team of clinicians, psychometricians, and behavioral researchers reviewed the instrument for measurement adequacy [1].
• Sampling: Diverse populations (N=919) aged ≥18 years from Atlanta, Georgia were included using venue-based sampling across 28 locations including churches, educational forums, health fairs, and community events [1].
• Statistical Analysis: The development process included exploratory factor analysis, principal components factor analysis with varimax rotation, and confirmatory factor analysis (RMSEA=.068; CFI=0.835) to verify item-factor relationships and determine construct validity [1].

Protocol 2: Digital Informed Consent Comprehension Assessment

A comprehensive cross-sectional study evaluated the effectiveness of electronic informed consent (eIC) materials across Spain, the United Kingdom, and Romania [2].

Digital Consent Comprehension Assessment Workflow:

Methodological Details:

• Material Development: eIC materials were developed following i-CONSENT guidelines using a cocreation process with target populations. A multidisciplinary team including clinical trial physicians, epidemiologists, a sociologist, a journalist, and a nurse collaborated on the design [2].
• Formats Offered: Participants could choose from multiple formats including layered web content (modular approach with clickable definitions), narrative videos (storytelling format for minors, question-and-answer for pregnant women), printable documents with integrated images, and infographics simplifying complex topics [2].
• Assessment Tool: Researchers used an adapted version of the Quality of Informed Consent Questionnaire (QuIC) with three tailored versions for each population. The surveys consisted of two parts: Part A measured objective understanding (22 questions with "no," "don't know," and "yes" responses), while Part B measured subjective understanding using a 5-point Likert scale [2].
• Scoring Protocol: Objective comprehension was categorized as low (<70%), moderate (70%-80%), adequate (80%-90%), or high (≥90%). Satisfaction was measured using Likert scales and usability questions, with scores ≥80% considered acceptable [2].
• Statistical Analysis: Multivariable regression models identified predictors of comprehension, adjusting for demographic factors and prior trial experience [2].

Key Findings from Comprehension Research

Quantitative Assessment Outcomes

Table 2: Comprehension Outcomes Across Assessment Methods

Assessment Method	Population	Sample Size	Comprehension Rate	Key Predictive Factors	Satisfaction Rates
Digital Informed Consent (eIC) [2]	Minors	620	83.3% (mean)	Gender (girls outperformed boys)	97.4%
	Pregnant Women	312	82.2% (mean)	Prior trial experience (negative association)	97.1%
	Adults	825	84.8% (mean)	Generation X outperformed Millennials	97.5%
CRIS Instrument [1]	Diverse adults	919	Not directly measured	Subjective norms (α improved from 0.525 to 0.850 after rewording)	Not measured
ClinicalTrials.gov vs. Publication Comparison [3]	Trial results	110	20% had inconsistent primary outcome values	Industry sponsorship; earlier submission dates	Not applicable

Research revealed significant differences in format preferences across populations:

• Minors: 61.6% (382/620) preferred video formats for consent information [2]
• Pregnant Women: 48.7% (152/312) preferred video formats [2]
• Adults: 54.8% (452/825) favored text-based materials [2]

These preferences highlight the importance of offering multiple formats to accommodate different learning styles and demographic factors. The study also found that materials co-created in Spain were effective across countries but yielded higher comprehension within the original target population, emphasizing the importance of cultural adaptation [2].

Table 3: Research Reagent Solutions for Comprehension Assessment

Tool/Resource	Primary Function	Application Context	Key Features	Validation Requirements
CRIS Instrument [1]	Measures attitudes and beliefs toward clinical trial participation	Pre-recruitment assessment; diversity initiatives	41-item scale measuring 8 theoretical domains; 5-point Likert scale	Confirmatory factor analysis; reliability testing (α ≥0.70)
Adapted QuIC Questionnaire [2]	Assesses objective and subjective comprehension of consent information	Post-consent evaluation; consent process improvement	22-item objective assessment; 5-point subjective scale	Population-specific validation; cross-cultural adaptation
Digital Consent Platform [2]	Presents consent information in multiple accessible formats	Decentralized trials; diverse population recruitment	Layered information, videos, infographics, printable documents	Usability testing; comprehension validation across formats
Scale Development Protocol [4]	Framework for developing new assessment instruments	Novel construct measurement; instrument adaptation	3-phase, 9-step approach (item development, scale construction, evaluation)	Content validity; factor analysis; reliability and validity testing

Implications for Clinical Trial Research and Practice

The comprehensive assessment of understanding deficits in clinical trial participants reveals several critical considerations for researchers and drug development professionals. First, the high reliability of the CRIS instrument (Cronbach's α ranging from 0.734–0.918 across subscales) demonstrates that theoretically-grounded scales can effectively measure complex constructs influencing trial participation [1]. This is particularly valuable for designing targeted recruitment strategies for underrepresented populations.

Second, the consistently high comprehension scores (exceeding 80%) achieved with digitally delivered, co-created consent materials indicates that traditional consent processes can be significantly improved through participant-centered design [2]. The negative association between prior trial participation and comprehension scores further suggests that experienced participants may develop overconfidence, highlighting the need for tailored engagement strategies for returning research participants.

Finally, the discrepancies between ClinicalTrials.gov results and journal publications [3], particularly regarding adverse event reporting (with 87% of inconsistent trials reporting more serious adverse events in ClinicalTrials.gov), underscore the importance of transparent reporting practices and comprehensive data accessibility for truly informed consent.

These findings collectively emphasize that measuring and addressing understanding deficits requires multi-faceted approaches combining validated assessment instruments, participant-centered communication strategies, and transparent reporting practices throughout the research lifecycle.

Demystifying Randomization in Clinical Trials

Randomized Controlled Trials (RCTs) are considered the gold standard for evaluating new treatments, yet the principles and purpose of randomization are often misconstrued [5]. Understanding its true function is fundamental to interpreting trial results accurately.

Core Principles and Common Misconceptions

Table: Randomization Methods in Clinical Trials

Method	Core Principle	Key Advantage	Key Limitation	Ideal Use Case
Simple Randomization [6]	Allocates subjects using a simple random process, like a coin toss.	Eliminates bias by eliminating predictability; complete randomness.	High probability of group size imbalance in small samples.	Large-scale trials where chance imbalance is minimal.
Block Randomization [6]	Random allocation occurs within small, predefined blocks (e.g., blocks of 4 or 6).	Ensures near-equal group sizes throughout the trial; increases comparability.	Risk of selection bias if block size is known and predictable.	Small to medium-sized trials where balance is critical.
Stratified Randomization [6]	Participants are first grouped by key prognostic factors (e.g., age, disease severity), then randomized within these strata.	Balances important prognostic factors across groups; increases statistical power.	Becomes impractical with too many strata, leading to sparse data.	When one or two known factors strongly influence the outcome.
Adaptive Randomization [6]	Allocation probability changes based on accumulating trial data (e.g., response to therapy).	Can maximize the number of patients receiving the beneficial treatment.	Increased complexity in design and analysis; requires careful management.	Often used in later-phase trials or for rare diseases.

A critical and widespread misconception is that randomization aims to create groups that are perfectly balanced on all known and unknown patient characteristics at the start of a trial. This is not the case. The true purpose of randomization is to eliminate selection bias by ensuring that each patient has a known, usually equal, chance of being assigned to any treatment group. This process creates groups that are comparable on average, but any particular randomization can, by chance, lead to some imbalance [7] [6]. The strength of randomization lies not in guaranteeing perfect balance for a single trial, but in ensuring that any such imbalances are due to chance alone, and statistical theory accounts for this uncertainty in the estimation of treatment effects [7].

Experimental Protocol: Implementing Stratified Block Randomization

The following workflow details a robust methodology for implementing a stratified block randomization, commonly used to ensure balance across key factors.

Title: Stratified Block Randomization Workflow

Step-by-Step Protocol:

• Define Prognostic Factors: Before the trial begins, identify 1-3 key patient characteristics known to strongly influence the primary outcome (e.g., study site, disease severity, gender) [6].
• Create Strata: Combine these factors to create all possible stratification groups. For example, using two sites and two disease severity levels creates 2 x 2 = 4 distinct strata.
• Generate Allocation Lists: For each stratum, an independent statistician generates a separate, computer-generated randomization sequence using random block sizes (e.g., varying between 4 and 6). Using varying block sizes helps minimize the predictability of the next assignment [6].
• Implement Allocation Concealment: The generated allocation sequences are stored in a secure, central system (e.g., an interactive web response system). Investigators cannot access the sequence before enrolling a participant, which prevents selection bias [6].
• Enroll and Assign: When a eligible participant is enrolled, the investigator accesses the central system and provides the participant's stratum information. The system then assigns the participant to a treatment group based on the next allocation in the sequence for that specific stratum.

The Scientist's Toolkit: Randomization Essentials

Table: Key Reagents and Tools for Randomization

Item	Function	Example
Interactive Web Response System (IWRS)	A central computer system that manages the allocation sequence, ensures allocation concealment, and assigns treatments in real-time.	Commercial systems like Oracle Clinical One, Medidata Rave.
Statistical Computing Software	Used to generate the randomization sequences (e.g., simple, block, stratified) and validate the process.	R (with randomizeR or blockrand packages), SAS (PROC PLAN).
Protocol Document	The master study document that pre-specifies the randomization method, allocation ratio, and any stratification factors.	Study Protocol.

Interpreting Risk in Pharmacoepidemiology

Comparing risk estimates between placebo-controlled RCTs and real-world observational studies is a common source of confusion, primarily due to fundamental differences in their design and the question they ask.

The Contrast: Efficacy vs. Comparative Safety

Table: Placebo RCTs vs. Active Comparator Observational Studies

Aspect	Placebo-Controlled RCT [8] [9]	Active-Comparator Observational Study [8]
Primary Question	"What is the efficacy and absolute safety of Drug A vs. no treatment?"	"What is the relative safety of Drug A vs. the standard treatment (Drug B)?"
Control Group	Placebo (inert substance)	Patients taking another active drug in the same class.
Key Challenge	May be unethical or unfeasible for some conditions; results may not reflect real-world use.	Confounding by indication: patients prescribed different drugs may have differing baseline risks.
Result Interpretation	Provides a estimate of the drug's net effect over placebo.	Provides evidence on the drug's safety profile relative to a common alternative.

A clear example is the investigation of the cardiovascular safety of the blood pressure medication Olmesartan. Initial RCTs in diabetic patients suggested an increased risk of cardiovascular death compared to placebo [8]. However, subsequent large observational studies compared Olmesartan initiators to initiators of other similar drugs (ARBs/ACEIs) and found little to no evidence of increased risk in the general user population [8]. This discrepancy does not necessarily mean one study is wrong; rather, they are answering different questions. The RCT answers "Is Olmesartan better than nothing?" while the observational study answers "Is Olmesartan safer than other available options?".

Experimental Protocol: Designing an Active Comparator New User Study

This protocol outlines the steps for a robust observational study design that minimizes confounding.

Title: Active Comparator New User Study Design

Step-by-Step Protocol:

• Cohort Definition: Clearly define the "drug of interest" group and the "active comparator" group, ensuring they are clinically plausible alternatives for the same indication [8].
• New-User Design: Include only patients who are starting the drug for the first time ("new users"). This avoids biases that can arise from including long-term users who have survived the early period of therapy [8].
• Data Source: Use a longitudinal healthcare database that captures prescriptions, diagnoses, procedures, and patient demographics (e.g., Clinical Practice Research Datalink) [8].
• Propensity Score (PS) Development: The PS is the probability of receiving the drug of interest given a patient's measured covariates. Estimate it using a model that includes all suspected confounders (e.g., age, comorbidities, healthcare utilization) [8].
• PS Implementation: Use the PS to create comparable groups. This can be done by matching each patient on the drug of interest to one or more patients on the comparator with a similar PS, or by weighting patients by their PS [8].
• Balance Assessment: Check that the measured covariates are balanced between the two groups after PS matching/weighting.
• Outcome Analysis: Compare the incidence of the safety outcome (e.g., cardiovascular death) between the two balanced groups using appropriate statistical models.

The Scientist's Toolkit: Risk Analysis Essentials

Table: Key Tools for Risk Analysis in Observational Studies

Item	Function	Example
Propensity Score	A statistical tool that summarizes all measured patient characteristics into a single score, allowing for the creation of comparison groups that are similar on all included covariates.	Calculated using logistic regression; used for matching or weighting.
High-Dimensional Databases	Large-scale healthcare databases that contain detailed records on prescriptions, medical encounters, and outcomes for large populations.	CPRD (UK), Medicare Claims (US).
High-Dimensional Propensity Score (hd-PS)	An algorithm that uses a large number of data-driven covariates from healthcare databases in addition to predefined confounders to improve control of confounding.	SAS or R algorithms for hd-PS.

Unraveling the Complexity of Placebo Effects

The placebo response is frequently oversimplified as a background "noise" to be subtracted out. Modern science reveals it is a complex, biologically active phenomenon that can interact with pharmacotherapy.

Placebo Response vs. Effect and Variability Across Disorders

It is crucial to distinguish between the observable placebo response (the overall health change in the placebo group, which includes statistical artifacts like regression to the mean) and the placebo effect (the psychobiological change specifically attributable to the therapeutic context and patient expectations) [10]. A meta-research study found that, on average, a significant 54% of the overall treatment effect in RCTs is attributable to these contextual effects, highlighting their substantial contribution to patient outcomes [10].

Furthermore, placebo effect sizes are not uniform; they vary dramatically across different mental disorders, as shown by an umbrella review of meta-analyses.

Table: Placebo Effect Sizes Across Mental Disorders

Mental Disorder	Standardized Effect Size (and 95% CI)	Magnitude	Key Correlates of larger placebo response
Generalized Anxiety Disorder [11]	d = 1.85 (1.61 to 2.09)	Very Large	Later publication year, more trial sites, larger sample size.
Major Depressive Disorder [11]	g = 1.10 (1.06 to 1.15)	Large	Increased baseline severity, larger active treatment effect.
Alcohol Use Disorder [11]	g = 0.90 (0.70 to 1.09)	Large	-
Restless Legs Syndrome [11]	g = 1.41 (1.25 to 1.56)	Large	-
Primary Insomnia [11]	g = 0.35 (0.28 to 0.42)	Small	-
Obsessive-Compulsive Disorder [11]	d = 0.32 (0.22 to 0.41)	Small	-
Schizophrenia Spectrum [11]	SMC = 0.33 (0.22 to 0.44)	Small	-

The Challenge of Non-Additivity

The conventional calculation of drug efficacy (Drug Response - Placebo Response) rests on the assumption of additivity: that the drug's effect and the placebo effect are independent and sum together. However, evidence challenges this. Factors like patient expectation can significantly modulate the drug's effect [9]. For instance, a study showed that the analgesic effect of remifentanil could be enhanced by positive expectation or completely abolished by negative expectation, demonstrating a clear drug-expectation interaction [9]. Similarly, the therapeutic context (e.g., branding, clinician demeanor) can alter outcomes in both drug and placebo arms, leading to non-additive effects [9].

Experimental Protocol: A 2x2 Factorial Design for Testing Additivity

This design allows researchers to disentangle the specific pharmacological effect of a drug from the contextual and expectation effects.

Title: 2x2 Factorial Design for Additivity

Step-by-Step Protocol:

• Intervention Design:
  • Pharmacological Factor: Active Drug vs. Placebo.
  • Contextual Factor: Enhanced Expectation vs. Neutral Expectation. The enhanced context might include a positive endorsement of treatment efficacy, branded packaging, and a therapeutic ritual, while the neutral context is minimal and non-suggestive [9].
• Randomization: Participants are randomly allocated to one of the four resulting cells, creating a 2 (Drug/Placebo) x 2 (Enhanced/Neutral) factorial design.
• Outcome Measurement: Measure the primary clinical outcome (e.g., pain score, asthma control) in all groups after the intervention period [9].
• Statistical Analysis: Analyze the data using a factorial ANOVA. A significant interaction term between the drug and contextual factors indicates non-additivity. This means the effect of the drug depends on the context in which it is delivered. If the effect of the active drug over its matched placebo is the same in both the enhanced and neutral contexts, it suggests additivity.

The Scientist's Toolkit: Placebo Research Essentials

Table: Key Reagents and Tools for Placebo Research

Item	Function	Example
Sham/Placebo Device	A physically identical but non-functional version of the active intervention (e.g., sham acupuncture, sham brain stimulation).	Critical for neurostimulation trials.
Validated Patient-Reported Outcome (PRO) Measures	Questionnaires that capture the subjective experience of symptoms (e.g., pain, fatigue), which are often most sensitive to placebo effects.	Visual Analog Scale for pain, Hamilton Rating Scale for Depression.
Scripted Physician-Patient Interactions	Standardized verbal instructions or conversations used to systematically manipulate patient expectations.	A positive vs. neutral script about treatment benefits [9].

Synthesis: Implications for Informed Consent Comprehension

Framing these concepts within informed consent comprehension is critical. Truly informed participants should understand that randomization aims for fairness but doesn't guarantee balance; that risk is relative to the comparator (placebo or another drug); and that their own beliefs and the clinical context can meaningfully influence their treatment outcomes. Modern consent processes are exploring digital and enhanced materials to better communicate these complex ideas, with studies showing that well-designed electronic informed consent (eIC) can achieve high comprehension and satisfaction rates among participants [12]. Effectively communicating these nuanced concepts is not just a regulatory requirement—it is a fundamental component of ethical and rigorous clinical science.

Demographic and Contextual Factors Influencing Comprehension Levels

Within the framework of measuring informed consent comprehension outcomes, a critical challenge emerges: the protection of participant autonomy is fundamentally dependent on their understanding of the research to which they consent. Empirical studies, however, consistently reveal that comprehension levels are often unsatisfactory, raising serious ethical questions about the validity of the consent process in both clinical practice and research [13] [14]. This guide provides a comparative analysis of how key demographic and contextual factors influence comprehension, synthesizing current empirical data to equip researchers, scientists, and drug development professionals with evidence-based strategies. The objective is to move beyond a one-size-fits-all compliance model toward a participant-centered approach that acknowledges and adapts to human diversity.

Comparative Analysis of Comprehension Factors

Comprehension of informed consent is not uniform across populations or settings. The following sections and comparative tables summarize the empirical evidence on how specific factors influence understanding.

Key Demographic Factors

Individual demographic characteristics significantly correlate with varying levels of comprehension. The table below synthesizes findings from recent studies.

Table 1: Influence of Demographic Factors on Informed Consent Comprehension

Factor	Impact on Comprehension	Supporting Evidence
Health Literacy	A dominant factor. Parents with limited health literacy scored significantly lower on comprehension assessments overall and across all domains (e.g., purpose, procedures, risks, alternatives) [15].	Mean comprehension score: 68.28 (Limited) vs. 79.24 (Adequate); β = -9.02, P < .001 [15].
Language	Use of a non-dominant language for medical communication is associated with lower comprehension. Spanish-speaking parents had lower overall comprehension and lower understanding of purpose, procedures, and voluntariness [15].	Mean comprehension score: 66.45 (Spanish) vs. 77.25 (English); β = -5.30, P = .01 [15].
Age	Mixed effects. One study found older participants preferred more detailed, original consent text over simplified versions [16] [17]. Another study on abortion research found no significant difference in comprehension between adolescents and adults [18].	Older participants were 1.95 times more likely to prefer the original text (P=.004) [16] [17]. Comprehension on 5 key principles was high (>87%) and equivalent across age groups [18].
Ethnicity & Cultural Context	Context-dependent impact. A study on parents of pediatric cancer patients found Hispanic ethnicity itself was not significant when controlling for health literacy and language [15]. However, a significant urban-rural divide in understanding voluntariness has been observed [14].	85% of urban vs. 21% of rural participants understood voluntary participation [14]. In a Tanzanian HIV vaccine trial, community misconceptions about vaccines presented a major comprehension barrier [19].

Key Contextual and Study Design Factors

The context of the research and the design of the consent process itself are equally critical in shaping comprehension outcomes.

Table 2: Influence of Contextual and Study Design Factors on Informed Consent Comprehension

Factor	Impact on Comprehension	Supporting Evidence
Consent Modality (e.g., Telehealth)	No significant difference in comprehension or decision-making control between teleconsent and traditional in-person methods, suggesting telehealth is a viable alternative that overcomes geographic barriers [20].	No significant differences in QuIC (Quality of Informed Consent) Part A (P=.29), Part B (P=.25), or DMCI (Decision-Making Control Instrument) scores (P=.38) between groups [20].
Information Presentation	Shorter text length and improved readability are strongly preferred and enhance understanding. Participants were less likely to prefer original consent text as its length increased, particularly for sections explaining study risks [16] [17].	For every unit increase in character length, participants were 1.20 times more likely to prefer the modified, shorter text (P=.04) [16] [17].
Study Incentives	Can indirectly influence voluntariness and the decision to withdraw, even when comprehension is adequate. Participants may feel reluctant to leave a study due to the loss of ancillary benefits [19].	In an HIV trial, incentives like health insurance, free condoms, and medical checkups influenced participants' reluctance to withdraw, despite their comprehension of the right to do so [19].
Informed Consent Components	Comprehension levels vary drastically for different elements of the consent form. Understanding of voluntariness and withdrawal is generally high, while grasp of randomization, placebos, and risks is often poor [14].	A systematic review found >75% understood voluntariness and withdrawal, but only a small minority understood placebo concepts (13-49%), randomization, and risks (as low as 7%) [14].

Detailed Experimental Protocols

To ensure the reproducibility of comprehension research, this section outlines the methodologies of two key studies cited in this guide.

Protocol 1: Randomized Controlled Trial on Teleconsent

Objective: To evaluate the effectiveness of telehealth versus in-person informed consent on participant comprehension and decision-making [20].

• Study Design: Randomized comparative study.
• Participants: 64 participants recruited for a parent study on patient portals. They were randomly assigned to teleconsent (n=32) or in-person consent (n=32) groups.
• Intervention:
  • Teleconsent Group: Used Doxy.me software for real-time interaction with researchers while reviewing and electronically signing documents.
  • In-Person Group: Traditional face-to-face consent process.
• Measures:
  • Quality of Informed Consent (QuIC): A validated survey measuring objective comprehension of the consent form.
  • Decision-Making Control Instrument (DMCI): Assessed perceived voluntariness, trust, and decision self-efficacy.
  • Short Assessment of Health Literacy-English (SAHL-E): Measured participants' health literacy levels.
• Analysis: Compared average scores for QuIC and DMCI between the two groups using statistical tests (t-tests, reported P-values).

Protocol 2: Cross-Sectional Study on Social Determinants of Health

Objective: To assess whether social determinants of health (SDOH) and sociocontextual factors are associated with parental comprehension of informed consent in therapeutic childhood cancer clinical trials [15].

• Study Design: Prospective cross-sectional study.
• Participants: 223 parents of children with newly diagnosed cancer who had provided informed consent for a therapeutic clinical trial within the previous week.
• Data Collection:
  • Participants completed questionnaires within one week of the consent discussion.
  • Primary Tool: The 20-item Quality of Informed Consent (QuIC) instrument, which provides an overall comprehension score and domain scores (purpose/procedures/randomization; risks/benefits; alternatives; voluntariness).
  • Covariates: Data on SDOH (marital status, language, education, employment, insurance, health literacy) and sociocontextual factors (ethnicity, satisfaction, cancer type) were collected via a sociodemographic questionnaire.
• Analysis: Linear mixed-effects models were used to assess associations between SDOH factors and QuIC comprehension scores, controlling for potential confounders.

Visualizing the Comprehension Framework

The following diagram illustrates the complex relationships and pathways through which demographic and contextual factors influence informed consent comprehension outcomes, integrating findings from the cited research.

This diagram shows that comprehension is not a direct result of single factors, but the outcome of a process mediated by engagement, understanding, and trust. This systems-view explains why a multi-faceted approach is necessary for improvement.

The Scientist's Toolkit: Key Research Reagents

For researchers designing studies to measure or improve informed consent comprehension, the following tools and materials are essential.

Table 3: Essential Reagents for Informed Consent Comprehension Research

Tool/Reagent	Function	Application Example
Quality of Informed Consent (QuIC) Survey	A validated, quantitative instrument to objectively measure a participant's understanding of key consent elements, such as purpose, procedures, risks, benefits, and voluntariness.	Used as the primary outcome measure in both the telehealth [20] and SDOH [15] studies to obtain reliable comprehension scores.
Decision-Making Control Instrument (DMCI)	Assesses the participant's perception of voluntariness, trust in the research team, and self-efficacy in making the decision to participate.	Employed alongside the QuIC to provide a holistic view of both understanding and the quality of the decision-making process in the teleconsent trial [20].
Health Literacy Assessment Tool (e.g., SAHL-E)	A brief, validated screening tool to measure a participant's ability to read and understand common health terms.	Critical for stratifying participants by health literacy level to analyze its impact as an independent variable, as demonstrated in the pediatric cancer study [15].
Readability Analysis Software	Calculates the reading grade level and complexity of written consent documents using metrics like Flesch-Kincaid.	Used by researchers to systematically create simplified, "modified" versions of consent text for comparative preference testing [16] [17].
Digital Consent Platforms (e.g., Doxy.me)	Enables remote, real-time consent processes via videoconferencing, often with integrated e-signature functionality.	Served as the intervention platform for the teleconsent group, proving its functional equivalence to in-person methods [20].

The empirical evidence unequivocally demonstrates that informed consent comprehension is not a monolithic outcome but a variable one, significantly shaped by a complex interplay of demographic and contextual factors. While elements like health literacy and language consistently show a strong direct correlation with understanding, other factors like age and ethnicity exert their influence through more complex cultural and contextual pathways. Furthermore, the design of the consent process itself—its length, readability, and modality—is a powerful, modifiable factor under the researcher's control. A successful strategy for improving comprehension outcomes requires a shift from mere regulatory compliance to a genuinely participant-centered approach. This involves proactively using validated tools to assess comprehension, tailoring communication to address diverse health literacy and language needs, and simplifying consent materials without sacrificing critical information. By integrating these evidence-based practices, the research community can uphold the ethical principle of respect for persons and ensure that consent is truly informed.

Informed consent serves as the cornerstone of ethical clinical research, bridging the fundamental principles of respect for person autonomy and the scientific validity of study outcomes [21] [22]. The ethical imperative of informed consent extends beyond mere regulatory compliance—it represents a fundamental commitment to upholding the dignity and rights of research participants while simultaneously ensuring the integrity of collected data [22]. When research volunteers inadequately understand the nature, risks, and benefits of their participation, both ethical and scientific foundations are compromised [23]. Studies reveal alarming comprehension deficits among research participants; for instance, one investigation of cancer trial participants found that 70% did not recognize the unproven nature of the study drug [23]. This comprehensive analysis examines the critical connection between comprehension assessment, autonomous decision-making, and research validity, providing researchers with methodological approaches and empirical evidence to strengthen informed consent processes in clinical trials.

Theoretical Framework: Connecting Comprehension to Ethical Principles

The Triad of Valid Informed Consent

Valid informed consent rests upon three essential elements that must be present simultaneously [21]:

• Voluntarism: The participant's decision must be free from coercion, undue influence, or manipulation, enabling an autonomous choice based on personal values and circumstances [21].
• Adequate Information Disclosure: Researchers must provide comprehensive, understandable information about the study's purpose, procedures, risks, benefits, and alternatives [21].
• Decision-Making Capacity: The participant must possess the cognitive ability to understand, appreciate, reason with the provided information, and express a choice [21].

These elements collectively ensure that consent is not merely a signed document but an ongoing process of understanding and voluntary participation [24].

Ethical Foundations and Regulatory Evolution

The contemporary understanding of informed consent has evolved through decades of ethical deliberation, notably crystallized in the Belmont Report's principles [25]:

• Respect for Persons: Acknowledges the autonomy of individuals and requires protecting those with diminished autonomy [25].
• Beneficence: Obligates researchers to minimize potential harms and maximize benefits [25].
• Justice: Demands fair distribution of research burdens and benefits across participant populations [25].

These principles inform current regulatory frameworks, including the Common Rule and FDA regulations, which mandate specific elements that must be included in consent processes [24].

Figure 1: Theoretical Pathway from Ethical Foundations to Research Outcomes

Experimental Evidence: Measuring Comprehension Outcomes

Consent Form Simplification Studies

Experimental Protocol: A controlled study investigated the impact of consent form length and complexity on participant comprehension [23]. Researchers randomized healthy volunteers for a phase I bioequivalence study to receive either a standard 14-page consent form (5,716 words) or a concise 4-page version (2,153 words) [23]. The simplified form eliminated repetition and unnecessary detail while using more accessible language, reducing the Flesch-Kincaid reading level from 8.9 to 8.0 [23]. Both forms contained all federally required elements, but the concise version emphasized clear, straightforward language [23].

Quantitative Findings: The study employed a 15-item multiple-choice questionnaire administered immediately after consent form review to assess understanding of research purpose, procedures, risks, benefits, and rights [23]. Comprehension scores were calculated based on correct answers, with possible scores ranging from 0-15 [23]. While the primary hypothesis suggested equivalent comprehension between groups, the study powerfully demonstrated that streamlined disclosure documents could maintain understanding while potentially enhancing satisfaction [23].

Multimedia and Innovative Consent Interventions

Audio-Visual Intervention Protocol: A systematic review of 16 randomized and quasi-randomized trials (1,884 total participants) evaluated audio-visual information presentations compared to standard consent processes [26]. Studies employed various media formats including computers, DVDs, videos, and CD-ROMs with components such as professional voice-overs, patient testimonials, and multimodal explanations of technical concepts [26]. Some interventions supplemented rather than replaced traditional written consent [26].

Pictorial Consent Protocol: Research in low-literacy settings such as Sierra Leone developed and evaluated pictorial 'information and consent' (PIC) sheets for school-based oral health surveys [27]. Local collaborators worked with illustrators to create visual representations of research procedures [27]. Evaluation involved 500 participants (children and parents) who provided feedback via five-point Likert scales assessing both satisfaction with visuals and their effectiveness in aiding understanding [27].

Electronic Consent Innovation: A 2022 study used provocative design prototypes ("provotypes") to explore patient preferences for electronic informed consent (eIC) systems [28]. Through 30 interviews with clinical trial participants, researchers identified key design considerations including trust factors, personalization options, and preferences for ongoing communication features [28]. Participants expressed interest in understanding assessment tools and tailored information delivery [28].

Comparative Effectiveness of Consent Interventions

Table 1: Quantitative Outcomes of Consent Intervention Studies

Intervention Type	Comprehension Impact	Satisfaction Outcomes	Participation Effects	Evidence Quality
Consent Form Simplification [23]	Equivalent comprehension scores between standard and concise forms	Increased satisfaction with concise forms	Not specifically measured	High (actual trial context)
Audio-Visual Interventions [26]	Slight improvement in knowledge/understanding	Improved satisfaction with information provided	Little to no difference in participation rates	Low to very low (hypothetical scenarios in some studies)
Pictorial Aids (Low-Literacy) [27]	High understanding ratings (4.87/5)	High satisfaction with visuals (4.83/5)	Not specifically measured	Moderate (real-world setting, limited validation)
Electronic Informed Consent [28]	Positive views on integrated understanding assessments	Desire for personalized communication options	Willingness to share data for research advancement	Preliminary (design phase research)

Assessment Methodologies: Measuring Comprehension Outcomes

Validated Assessment Instruments

Quality of Informed Consent (QuIC) Questionnaire: Spanish researchers developed and validated a comprehensive patient-reported questionnaire to evaluate the informed consent process from the participant perspective [29]. The instrument underwent rigorous development including literature review, item generation, expert review, pilot testing, and readability analysis [29]. The final questionnaire includes four sections assessing: (1) socio-demographic data; (2) practical aspects of consent process implementation; (3) patient satisfaction, expectations and motivations; and (4) understanding level [29]. The reading ease analysis yielded a Flesch-Szigriszt index of 64.34, indicating "average difficulty" on the Inflesz scale [29]. Pilot testing with 32 patients demonstrated good comprehensibility and an average completion time of 16.6 minutes [29].

Multi-Domain Comprehension Assessment: The Pfizer-NIH substudy employed a 15-item multiple-choice instrument focusing on essential consent elements required by federal regulations [23]. The assessment evaluated understanding across four critical domains: (1) recognition of research participation and its voluntary nature; (2) study purpose and procedures; (3) potential risks and benefits; and (4) confidentiality protections [23]. The questionnaire was developed through comprehensive literature review, iterative draft development with investigator input, and pretesting with healthy volunteers [23].

Emerging Assessment Approaches

Electronic Consent Comprehension Testing: Research into electronic informed consent systems has explored built-in understanding assessment tools that can be integrated into the consent process [28]. These digital assessments can provide immediate feedback to researchers about participant comprehension gaps and allow for targeted re-explanation of complex concepts [28].

Multi-method Evaluation Frameworks: Contemporary research recommends combining quantitative metrics with qualitative feedback mechanisms to obtain comprehensive understanding of participant comprehension [29] [27]. This approach captures both objective understanding levels and subjective experiences of the consent process.

Figure 2: Comprehension Assessment Methodologies and Outcome Measures

The Researcher's Toolkit: Essential Instruments for Consent Comprehension Research

Table 2: Key Research Reagents and Assessment Tools for Consent Comprehension Studies

Tool/Instrument	Primary Function	Application Context	Implementation Considerations
QuIC Questionnaire [29]	Assess patient-reported understanding and satisfaction	Clinical trial settings; available in Spanish and English	Requires 16.6 minutes average completion time; appropriate for various literacy levels
Structured Multiple-Choice Tests [23]	Objective measurement of specific knowledge domains	Randomized trials of consent interventions	15-items covering key consent elements; immediate administration after consent review
Pictorial Consent Aids [27]	Enhance understanding in low-literacy populations	Resource-limited settings; pediatric research	Requires cultural adaptation and local validation; high participant satisfaction reported
Electronic Consent (eIC) Platforms [28]	Digital consent with integrated understanding assessment	Clinical trials with remote components; tech-savvy populations	Must address trust and data security concerns; allows personalization
Five-Point Likert Scales [27]	Measure subjective satisfaction and perceived understanding	Intervention feedback collection	Visual analog scales effective for diverse age groups and literacy levels
Audio-Visual Presentations [26]	Multimedia explanation of complex concepts	Studies with technical procedures; heterogeneous populations	Can supplement written consent; variable evidence for comprehension improvement

Implications for Research Validity and Ethical Practice

Direct Connections Between Comprehension and Data Quality

Adequate comprehension directly impacts research validity through multiple mechanisms:

• Protocol Adherence: Participants who understand study requirements are more likely to comply with intervention protocols and follow-up procedures [21].
• Data Accuracy: Comprehensive understanding of symptom reporting requirements and data collection procedures enhances the reliability of collected data [22].
• Retention Rates: Transparent communication during consent processes establishes trust that may improve participant retention throughout study duration [22].
• Adverse Event Reporting: Understanding of potential risks and reporting procedures enables timely identification of safety concerns [21].

Ethical Imperatives Beyond Regulatory Compliance

The connection between comprehension and autonomy represents more than mere regulatory fulfillment—it embodies the fundamental ethical commitment to respect persons as autonomous agents [22] [25]. When comprehension is compromised, so too is the validity of consent, reducing participants to mere means to research ends rather than willing partners in scientific advancement [21]. This ethical breach simultaneously undermines the social value of research by eroding public trust in scientific institutions [22].

The empirical evidence clearly demonstrates that informed consent comprehension is not an abstract ethical ideal but a measurable variable with direct implications for both participant autonomy and research validity [23] [21] [22]. While no single intervention strategy shows universal effectiveness across all populations, the accumulating research indicates that tailored, participant-centric approaches—whether through simplified documents, visual aids, or electronic systems—can significantly enhance understanding and satisfaction [23] [26] [27]. The continuing ethical imperative for researchers is to implement robust comprehension assessment as an integral component of consent processes and to utilize these outcomes to continually refine communication strategies. Only through such committed attention to comprehension measurement can the field fully honor the connected principles of respect for persons, beneficence, and justice while simultaneously advancing methodologically rigorous clinical research.

Assessment Tools and Techniques: Measuring Understanding Effectively

Within clinical research, ensuring that participants truly understand what they are consenting to is a fundamental ethical requirement. However, studies have consistently shown that participants often have poor comprehension of clinical trial information, with one review finding that only about half of participants adequately understood key elements like study risks, benefits, and the process of randomization [30]. This gap underscores the critical need for robust, validated instruments to accurately assess comprehension outcomes in informed consent research. This guide objectively compares assessment tools and methodologies, providing researchers with the data needed to evaluate participant understanding.

Core Instruments and Methodologies for Comprehension Assessment

A variety of tools and interventions have been developed to measure and improve comprehension. The following table summarizes the primary categories and their effectiveness based on systematic reviews.

Assessment Category	Description	Key Findings on Understanding
Enhanced Consent Forms [30]	Re-design of standard documents to improve readability and structure (e.g., simplified language, better formatting).	Most effective intervention; significant increase in understanding scores (SMD 1.73, 95% CI, 0.99 to 2.47) [30].
Extended Discussions [30]	Additional one-on-one time with a researcher to explain information and answer questions.	Significantly improves understanding (SMD 0.53, 95% CI, 0.21 to 0.84); 50% of tested interventions showed significant improvement [30].
Multimedia Approaches [30]	Use of video, interactive digital content, or computer-based modules to convey information.	Associated with a non-significant increase in understanding (SMD 0.30, 95% CI, -0.23 to 0.84); 31% of interventions showed significant improvement [30].
Test/Feedback Quizzes [30]	Participants take a knowledge test and receive immediate corrective feedback.	An effective method; 33% of tested interventions showed a significant improvement in participant understanding [30].
Electronic Consent (eConsent) [31]	Comprehensive digital platforms that often incorporate multimedia, interactivity, and quizzes.	Systematic review shows eConsent significantly improved understanding of clinical trial information and was rated as more acceptable and usable than paper-based consent [31].

The Reading Strategy Assessment Tool (RSAT)

The Reading Strategy Assessment Tool (RSAT) is a computer-based assessment designed to measure comprehension processes as they occur during reading, unlike traditional post-reading tests [32]. Its methodology is grounded in discourse comprehension theory, which posits that deep understanding relies on generating bridging and elaborative inferences to build a coherent mental model of the text [32].

Experimental Protocol for RSAT [32]:

• Procedure: Participants read text passages one sentence at a time on a computer.
• Prompting: At pre-selected target sentences, the presentation pauses, and the participant is prompted with a question.
• Question Types:
  • Direct Questions: Specific "wh-" questions (e.g., "Why did X happen?") designed to assess the reader's emerging comprehension of the text. Responses are coded for the number of content words that match an ideal answer.
  • Indirect Questions: Open-ended prompts (e.g., "What are you thinking regarding your understanding of the sentence?") intended to elicit the reader's spontaneous thoughts. Responses are analyzed for words associated with comprehension processes like paraphrases, bridging inferences, and elaborations.
• Data Interpretation: The frequency and quality of these processes, derived from the responses, are used to predict overall comprehension skill, with studies showing RSAT variables correlate with standardized test scores [32].

Visualizing the Informed Consent Comprehension Research Workflow

The following diagram illustrates a generalized experimental workflow for assessing informed consent comprehension, integrating tools like RSAT and various interventions.

The Researcher's Toolkit: Key Instruments and Reagents

This table details essential "research reagents"—the core tools and methods required for conducting rigorous informed consent comprehension research.

Tool/Item	Primary Function in Research
Validated Questionnaires	Quantitative assessment of immediate knowledge retention and long-term understanding after the consent process [30].
RSAT (Software-Based)	Provides real-time, process-oriented data on how participants comprehend consent information sentence-by-sentence, capturing inference generation [32].
eConsent Platform	A digital intervention tool that delivers consent information via multimedia, interactivity, and built-in quizzes; also facilitates data collection on engagement metrics [31].
Multimedia Modules	Audio-visual components used as an independent variable to test if they improve understanding and engagement compared to text-alone formats [30].
Enhanced Consent Document	The modified written material, often featuring improved readability, graphics, and simplified structure, which is tested against a standard consent form [30].
Scoring Rubrics (e.g., DISCERN, JAMA)	Standardized criteria to objectively evaluate the quality, accuracy, and reliability of health information, including consent materials or AI-generated content [33].
Readability Formulas (e.g., Flesch-Kincaid)	Algorithms that calculate the approximate U.S. grade level required to understand a text segment, used to ensure consent forms are accessible [33].

The choice of assessment instrument is paramount in informed consent comprehension research. While traditional post-reading questionnaires remain valuable, evidence shows that enhanced consent forms and extended discussions are particularly effective. Emerging tools like RSAT offer a deeper, process-oriented view of comprehension, and digital eConsent platforms show significant promise for improving understanding, engagement, and data quality. Researchers are equipped to select the most valid and reliable methods, ultimately upholding the ethical principle of informed consent.

Evaluating participant comprehension is a cornerstone of ethical research, particularly in studies involving informed consent. The choice between structured (quantitative) and open-ended (qualitative) questioning methodologies directly influences the depth, reliability, and applicability of data on participant understanding. Within informed consent comprehension outcomes research, this balance is critical; it ensures that consent is not merely a procedural formality but a genuinely informed and autonomous decision. Researchers and drug development professionals must therefore strategically employ these methods to capture both objective metrics of understanding and the rich, contextual insights into participant perception and reasoning.

Structured questioning, typically employing closed-formats like multiple-choice questions, provides standardized, easily comparable data suitable for statistical analysis. Conversely, open-ended questioning, through interviews or free-text responses, unveils the underlying thought processes, misconceptions, and qualitative aspects of comprehension that structured formats might miss [34] [35]. The emerging consensus is that a mixed-methods approach provides the most comprehensive evaluation, as it quantifies comprehension levels while also exploring the reasons behind those levels [36] [37]. This guide objectively compares the performance of these questioning approaches, supported by experimental data and detailed methodologies, to inform best practices in clinical research and drug development.

Theoretical Frameworks and Task Models

The effectiveness of any questioning method is underpinned by how individuals process information and understand task demands. In reading comprehension research, models like the Multiple-Document Task-Based Relevance Assessment and Content Extraction (MD-TRACE) and the Reading as Problem-Solving (RESOLV) model posit that successfully answering questions begins with constructing an accurate "task model" [38]. This mental representation of what the question requires is a critical initial step that influences all subsequent processes, from information retrieval to the final answer formulation [38].

Research indicates that a reader's ability to build this model varies. Skilled comprehenders tend to construct task models based on semantic cues, leading to a deeper understanding of the question's intent. In contrast, less-skilled comprehenders often rely on superficial, literal wording, making them more susceptible to misinterpretation, especially when question phrasing is complex or misleading [38]. This has direct implications for informed consent research, where ensuring all participants, regardless of health or data literacy, understand the questions about the study is paramount to obtaining valid comprehension data. Interventions like fixed timing (preventing participants from rushing) and quizzing on consent form content have been shown to improve task-model construction and, consequently, comprehension scores [34].

Conceptual Workflow of Comprehension Assessment

The following diagram illustrates the core mental process a participant uses to understand and answer a question about informed consent materials, based on the MD-TRACE and RESOLV models.

Experimental Comparison of Questioning Methodologies

Quantitative Data on Questioning Interventions

Recent empirical studies have directly tested the efficacy of various interventions, including questioning styles and procedural changes, on the comprehension of informed consent materials. The table below summarizes key quantitative findings from controlled experiments.

Table 1: Experimental Data on Interventions for Consent Comprehension

Intervention	Experimental Design	Key Quantitative Finding	Effect on Comprehension
Fixed Timing & Quizzing [34]	Between-participants (N=510); 2x2x2 design (Length, Timing, Quiz).	Fixed timing and a comprehension quiz led to significantly greater instruction-following (p<.001).	Significant Increase
Consent Form Length [34]	Between-participants; Short (141 words) vs. Long (752 words) forms.	Consent form length had no statistically significant effect on comprehension.	No Significant Effect
Alternative Delivery Formats [34]	Between-participants (N=182); 2x3 design (Length, Delivery Format).	Live and audiovisual formats increased comprehension compared to standard written text.	Significant Increase
Enhanced Consent Documents [37]	Systematic Review of 39 RCTs.	Enhanced documents (e.g., simplified text, infographics) significantly increased understanding (SMD: 1.73, 95% CI: 0.99, 2.47).	Significant Increase

Performance Analysis: Structured vs. Open-Ended Approaches

The performance of structured and open-ended questioning can be analyzed by examining their respective strengths and limitations in capturing different dimensions of informed consent comprehension.

Table 2: Performance Comparison of Questioning Methodologies

Feature	Structured Questioning	Open-Ended Questioning
Data Type	Quantitative, numerical scores.	Qualitative, textual and thematic data.
Primary Strength	Standardization, scalability, and objective comparison across populations.	Uncovers nuances, reasoning, and unforeseen misconceptions.
Key Limitation	May miss complex misunderstandings; can be influenced by question-wording bias.	Difficult to analyze at scale; subject to interpretation in coding.
Ideal Use Case	Benchmarking comprehension levels against a threshold; large-scale trials.	Exploring the "why" behind poor comprehension; refining consent language.
Stakeholder Insights	Surrogates find written consent highly important, less concerned with length [36].	Reveals contextual factors like rural patients' travel burdens [35].

Detailed Experimental Protocols

To ensure the reproducibility of these findings, below are detailed methodologies for key experiments cited in this guide.

Protocol 1: Testing Interactive Consent Elements

This protocol is derived from a study testing the effects of timing, quizzing, and length on online consent comprehension [34].

• Objective: To evaluate the effects of fixed timing, comprehension quizzes, and consent form length on participants' understanding and instruction-following behavior.
• Design: A 2 (Length: short or long) × 2 (Timing: fixed or free) × 2 (Quiz: present or absent) between-participants design.
• Participants: 510 participants recruited from a university and an online platform (Qualtrics).
• Procedure:
  • Participants were randomly assigned to one of the eight experimental conditions.
  • They were presented with an online consent form for a study on "Adult Temperament Differences."
  • Fixed Timing Condition: Participants could not advance the screen until a set time (based on 250 words/minute) had elapsed.
  • Quiz Condition: After the consent form, participants answered three multiple-choice questions about the study's purpose, researchers, and withdrawal procedure.
  • Dependent Measures:
    • Behavioral Measure: Compliance with an embedded instruction within the consent form.
    • Comprehension: Two multiple-choice questions assessing understanding of risks and data usage.
• Analysis: Independent samples t-tests and analyses of variance (ANOVA) to compare effects across conditions.

This protocol outlines a mixed-methods approach used to understand differences in rural and urban cancer patients' clinical trial experiences [35].

• Objective: To understand the factors that influence clinical trial participation for rural compared to urban cancer patients.
• Design: Semi-structured interviews combining closed-ended and open-ended questions.
• Participants: 30 cancer patients (15 rural, 15 urban) currently enrolled in a treatment clinical trial.
• Procedure:
  • A PhD-level researcher conducted individual, 30-minute phone interviews, which were audio-recorded and transcribed.
  • Closed-ended questions: Participants rated the helpfulness of 18 pre-defined factors (e.g., travel time, transportation, telehealth) on a binary (helpful/not helpful) scale.
  • Open-ended questions: Participants elaborated on their closed-ended responses and discussed other components that eased their experience.
• Analysis:
  • Quantitative: Chi-square analyses compared the frequency of "helpful" ratings between rural and urban groups.
  • Qualitative: A directed content analysis was performed on transcripts. Researchers independently coded transcripts using a constant-comparison method to develop and refine themes.

Research Reagent Solutions: Tools for Comprehension Assessment

Selecting the right "reagents" or tools is fundamental to designing robust studies on informed consent comprehension. The following table details essential methodological components.

Table 3: Essential Research Reagents for Consent Comprehension Studies

Research Reagent	Function & Description	Application Example
Validated Comprehension Scales	Multi-item instruments with established reliability and validity to measure a specific construct (e.g., understanding of risks).	Using a scale like the Deaconess Informed Consent Comprehension Test to generate a quantitative comprehension score [39].
Semi-Structured Interview Guide	A flexible protocol containing key open-ended questions with probes to explore participant understanding in their own words.	Eliciting rich, qualitative data on why surrogates in the ICU felt a specific consent process was helpful [36] [35].
Question-About-the-Question (QaQ)	A tool to assess a participant's "task model" by having them select a paraphrase that best reflects a question's meaning before answering it [38].	Measuring whether participants understood what a consent question was asking before evaluating their answer.
Codebook for Qualitative Analysis	A structured document defining themes and codes derived from data, used to ensure consistency in analyzing open-ended responses.	Systematically coding interview transcripts from rural and urban patients to identify themes like "travel burden" or "trust in provider" [35].
Multimedia Consent Tools	Augmented consent materials, such as infographics or videos, used as an intervention to improve understanding.	Co-designing an infographic with ICU survivors and surrogate decision-makers to simplify complex platform trial information [37].

Integrated Comprehension Assessment Workflow

This diagram outlines a mixed-methods procedure for assessing informed consent comprehension, integrating both structured and open-ended elements based on the cited research.

The empirical evidence demonstrates that structured and open-ended questioning methodologies are not mutually exclusive but are complementary forces in informed consent research. Structured approaches provide the essential metrics to benchmark understanding and statistically evaluate interventions, while open-ended approaches deliver the critical context and depth needed to interpret those metrics and improve the consent process itself [36] [35] [38].

For researchers and drug development professionals, the implication is clear: a mixed-methods framework is the most rigorous path forward. This involves using quantitative scales to establish baseline comprehension and measure the impact of new consent formats (e.g., infographics, videos) [34] [37], while simultaneously employing qualitative interviews to understand participant reasoning, identify persistent areas of confusion, and ensure that consent communications are truly effective across diverse populations [35] [40]. By strategically balancing these approaches, the research community can move beyond mere compliance to foster genuine understanding, thereby upholding the highest ethical standards in clinical trials and drug development.

Informed consent serves as the ethical cornerstone of clinical research, designed to uphold participant autonomy. However, a single consent encounter at a trial's outset often fails to ensure sustained comprehension throughout the entire research journey. The dynamic nature of clinical trials, particularly complex platform trials and adaptive designs, means that study parameters may evolve, requiring participants to continually understand their involvement [41]. Furthermore, evidence suggests that participant comprehension of critical consent elements is frequently overestimated by research staff, creating a significant gap between assumed and actual understanding [42].

Integrating systematic comprehension checks at strategic intervals addresses these challenges by transforming consent from a one-time event into a continuous process. This approach recognizes that understanding may fluctuate due to factors such as illness progression, treatment effects, and the introduction of new trial information. For research teams, this paradigm shift requires implementing structured assessments from pre-consent through post-trial feedback, ensuring participants maintain genuine understanding of their role, rights, and the research's nature throughout their entire engagement with the study [12] [43].

Comprehension Checkpoints: Integrating Assessment Across the Trial Timeline

The informed consent process should be conceptualized as a continuous cycle rather than a discrete event. The following diagram maps key comprehension checkpoints across the three fundamental phases of the clinical trial journey, highlighting opportunities for assessment and intervention.

Experimental Protocols for Comprehension Assessment

Protocol 1: Co-Design and Pre-Testing of Consent Materials

Objective: To develop and validate participant-centered consent materials before their implementation in clinical trials.

Methodology: This mixed-methods approach combines qualitative co-design with quantitative validation [41] [12]. The process begins with design thinking sessions involving target population representatives (e.g., patients, caregivers) to identify information priorities and preferred communication formats. Researchers then create multimodal consent tools (infographics, videos, layered digital content) based on this input. These materials undergo iterative pilot testing using validated comprehension assessment tools like the Quality of Informed Consent (QuIC) questionnaire [12].

Key Metrics: Comprehension scores across participant subgroups, format preference percentages, and qualitative feedback on clarity and usability.

Implementation Context: Particularly crucial for complex trials and vulnerable populations. In a study with minors and pregnant women, this approach resulted in comprehension scores exceeding 80% across all groups by tailoring materials to specific needs and preferences [12].

Protocol 2: Multimodal Consent Delivery with Immediate Comprehension Verification

Objective: To assess initial understanding immediately following the consent encounter using multiple verification methods.

Methodology: This protocol employs a structured consent discussion supplemented with enhanced visual aids (e.g., infographics explaining platform trial design) [41]. Research coordinators receive specific training on discussing complex concepts and using the Teach-Back technique, where participants explain concepts in their own words [42]. Participants complete a brief comprehension assessment focusing on critical elements (randomization, risks, voluntary participation). For digital consent platforms, embedded quizzes with immediate feedback can clarify misunderstandings [12].

Key Metrics: Objective comprehension scores (categorized as low <70%, moderate 70-80%, adequate 80-90%, high ≥90%), subjective comprehension ratings, and specific concepts frequently misunderstood.

Implementation Context: Effectively implemented in high-stress environments like ICU settings [41] and across multicultural trial sites through properly translated and adapted materials [12].

Protocol 3: Longitudinal Comprehension Monitoring

Objective: To evaluate retention of consent information throughout trial participation and assess understanding of protocol modifications.

Methodology: This protocol institutes scheduled comprehension check-ins at key trial milestones (e.g., treatment phase transitions, major protocol amendments) [43]. It utilizes brief, focused assessments administered at clinic visits or digitally between visits. The protocol includes systematic result dissemination with comprehension verification, where participants receive lay summaries of trial findings and demonstrate understanding of implications [43].

Key Metrics: Comprehension retention rates, understanding of protocol changes, and satisfaction with ongoing communication.

Implementation Context: Essential for long-term studies and trials with adaptive designs where parameters may evolve. Research shows most participants expect results regardless of outcome, viewing this communication as essential for maintaining trust [43].

Comparative Performance of Assessment Methodologies

Table 1: Comprehension Assessment Outcomes Across Methodologies

Assessment Method	Population Context	Comprehension Outcomes	Participant Satisfaction	Key Challenges
Co-Designed Infographics [41]	ICU patients/SDMs in platform trials	86% received intervention; 94% consent rate; High questionnaire completion (88%)	RCs reported better engagement; Reduced perceived confusion	Limited eligible encounters (33%); High-stress environment barriers
Digital Consent (eIC) [12]	Minors, pregnant women, adults across 3 countries	Mean objective comprehension: 83.3% (minors), 82.2% (pregnant women), 84.8% (adults)	>90% satisfaction across all groups; 94.2% reported facilitated understanding	Cultural adaptation requirements; Lower scores in lower education subgroups
Enhanced Consent Documents [41]	Mixed populations from systematic review	Standardized mean difference in understanding: 1.73 (95% CI: 0.99, 2.47)	Not systematically quantified	Limited ICU/SDM evidence; Variable implementation quality
Traditional Consent Only [42] [44]	Various clinical populations	Research staff concerns: 56% worried about participant understanding	Patients overwhelmingly positive (contrary to staff concerns)	Readability issues (mean 13th grade level); Time constraints (40% of staff)

Population	Preferred Format	Predictors of Higher Comprehension	Predictors of Lower Comprehension	Cross-Cultural Variation
Minors (n=620) [12]	Videos (61.6%)	Female gender (β=+.16 to +.36)	Prior trial experience; Specific countries (UK, Romania)	Significant country differences (P<.001)
Pregnant Women (n=312) [12]	Videos (48.7%)	Not specified	Not specified	Effective with cultural adaptation
Adults (n=825) [12]	Text (54.8%)	Generation X (vs. Millennials; β=+.26, P<.001)	Prior trial participation (β=-.47 to -1.77)	Lower scores in Romania with lower education
Older Adults [45]	Combined formats	Higher education; No cognitive impairment	Lower education; Cognitive concerns; Advanced age	Cultural perceptions of consent purpose

Table 3: Research Reagent Solutions for Comprehension Assessment

Tool/Resource	Primary Function	Implementation Context	Evidence Base
Adapted QuIC Questionnaire [12]	Validated comprehension assessment across domains	Pre/post consent; Trial milestones	Modified versions validated for minors, pregnant women, adults
Co-Design Session Framework [41]	Participatory development of consent materials	Protocol development phase	Mixed-methods evaluation showing feasibility and acceptability
Digital Consent Platform [12]	Layered information delivery with embedded comprehension checks	Multicountry trials; Diverse populations	Cross-sectional evaluation (n=1,757) showing >80% comprehension
Teach-Back Protocol [42]	Real-time verification of understanding through participant explanation	Consent encounter; New procedure explanation	Qualitative studies showing improved clarity and trust
Readability Analysis Software [44]	Quantitative assessment of consent form complexity	Document development and review	Studies showing most forms exceed recommended grade levels
Multimodal Consent Library [41] [12]	Repository of visual aids, videos, and templates	Complex trial designs; Vulnerable populations	RCT evidence showing significantly improved understanding

Discussion and Future Directions

Integrating systematic comprehension checks throughout the trial journey represents a fundamental shift from perceiving consent as a one-time event to embracing it as an ongoing ethical dialogue. This approach acknowledges that understanding is not static, particularly in complex modern trials where designs are increasingly sophisticated [46]. The evidence demonstrates that tailored, multimodal approaches developed through co-design methodologies consistently achieve comprehension rates exceeding 80% across diverse populations [41] [12].

Future development should focus on standardizing metrics for comprehension assessment across research networks, enabling benchmarking and continuous improvement. Additionally, as trials become more global, cross-cultural validation of assessment tools will be essential. The promising field of digital consent platforms offers opportunities for embedded, real-time comprehension checks that can adapt to individual participant needs and provide immediate clarification [12].

What remains clear is that maintaining participant understanding is not merely an ethical obligation but a scientific necessity. Participants with a genuine understanding of their role contribute more meaningfully to research and are better protected throughout their trial participation. By implementing the structured approaches outlined in this guide, research teams can ensure that informed consent truly fulfills its ethical promise from a trial's beginning through to the dissemination of its results.

Within the evolving paradigm of modern clinical research, the informed consent process is being fundamentally redefined by digital and multimedia technologies. The traditional model, reliant on dense, text-heavy paper forms, has long been associated with significant comprehension gaps, often failing to achieve true understanding and voluntary participation. Electronic consent (eConsent) platforms emerge as a powerful intervention within this context, designed to enhance participant understanding through interactive, customizable multimedia components. Measuring informed consent comprehension outcomes is central to validating these tools, requiring rigorous research methodologies to quantify their impact on understanding, engagement, and satisfaction compared to traditional methods. This guide objectively compares the performance of digital approaches, focusing on experimental data that illuminates their efficacy in achieving the foundational ethical goal of informed consent: ensuring participants truly comprehend the research in which they are engaging.

Experimental Protocols in eConsent Comprehension Research

To objectively evaluate eConsent platforms, researchers employ structured experimental designs. The following are detailed methodologies from key studies cited in this guide, providing a framework for assessing comprehension outcomes.

Multicountry Cross-Sectional Evaluation (Fons-Martinez et al., 2025)

This study evaluated the effectiveness of eConsent materials developed following the i-CONSENT guidelines for diverse populations across Spain, the United Kingdom, and Romania [12].

• Objective: The primary aim was to assess participants’ comprehension of and satisfaction with tailored eConsent materials. Secondary objectives included identifying demographic predictors of comprehension and evaluating cross-cultural applicability [12].
• Population: The study enrolled 1,757 participants across three distinct groups: 620 minors (aged 12-13), 312 pregnant women, and 825 adults (comprising millennials and Generation X) [12].
• Intervention Development: Materials were cocreated through a participatory process. This involved design thinking sessions with minors and pregnant women, and online surveys with adults. A multidisciplinary team ensured scientific accuracy and cultural relevance. Materials were professionally translated and offered in multiple formats: layered web content, narrative videos (storytelling for minors, Q&A for pregnant women), printable documents, and infographics [12].
• Comprehension Assessment: Comprehension was measured using an adapted version of the Quality of the Informed Consent (QuIC) questionnaire, tailored for each population. The assessment yielded an objective comprehension score (categorized as low: <70%, moderate: 70-80%, adequate: 80-90%, or high: ≥90%) and a subjective comprehension score using a 5-point Likert scale [12].
• Satisfaction Measurement: Satisfaction and usability were evaluated through Likert scales and specific usability questions, with scores ≥80% deemed acceptable [12].

Systematic Review for Low-Resource Settings (2025)

This review adopted a systematic approach to assess the role of digital consent tools in enhancing comprehension in low-resource settings [47].

• Search Strategy: The researchers followed PRISMA guidelines, searching databases (PubMed, Embase, Scopus, Cochrane) up to August 2025 using terms such as "digital consent," "e-consent," and "low-resource settings" [47].
• Eligibility Criteria: The PICO framework was used. Studies were included if they focused on underserved populations (P), evaluated digital consent tools like multimedia or web-based systems (I), used traditional paper consent as a comparator (C), and reported outcomes on participation, comprehension, or documentation quality (O) [47].
• Study Selection and Synthesis: Two reviewers independently screened titles, abstracts, and full-text articles. A narrative synthesis was undertaken due to the heterogeneity of the included studies, with findings organized to highlight key outcomes and contextual challenges [47].

Quasi-Experimental Study on Interactive Digital Intervention (2025)

This study evaluated an Interactive Digital Intervention (IDI) for substance use prevention, demonstrating a methodology applicable to interactive health communication, including consent [48].

• Design: A quasi-experimental, pre-post design was adopted.
• Population: 768 senior high school students from 9 randomly selected schools were assigned to either an IDI group (n=379) or a traditional didactic (TD) group (n=389) [48].
• Intervention: The IDI group received a 6-unit web-based program with interactive features like videos, quizzes, and scenario-based discussions. The TD group received conventional textbook instruction [48].
• Outcome Measures: The study assessed knowledge, health literacy (functional, communicative, critical), and learner engagement (cognitive, emotional) through pre- and post-intervention assessments. Data were analyzed using paired t-tests and generalized estimating equations [48].

The workflow for these experimental approaches is summarized in the diagram below.

Quantitative Comparison of eConsent Performance

The efficacy of digital and multimedia consent tools is demonstrated through key performance indicators such as comprehension scores, satisfaction rates, and operational efficiency. The data below summarize findings from controlled studies and systematic reviews.

Table 1: Comparative Comprehension and Satisfaction Outcomes

Study & Population	Intervention Type	Comparison Group	Objective Comprehension (Mean Score)	Satisfaction Rate	Key Findings
Multicountry Minors(n=620) [12]	Cocreated eIC (Video, Web, Docs)	Not Directly Tested	83.3%	97.4% (604/620)	61.6% of minors preferred video format.
Multicountry Pregnant Women(n=312) [12]	Cocreated eIC (Video, Infographics, Q&A)	Not Directly Tested	82.2%	97.1% (303/312)	48.7% of pregnant women preferred video format.
Multicountry Adults(n=825) [12]	Cocreated eIC (Web, Infographics, Docs)	Not Directly Tested	84.8%	97.5% (804/825)	54.8% of adults preferred text-based formats.
Malawi Pilot(n=109) [47]	Offline Tablet-Based eConsent	Paper-Based Consent	Not Specified	Not Specified	Eliminated documentation errors vs. 43% error rate in paper forms.
Nigeria Rural Population(n=42) [47]	Multimedia Consent (Audio-Visual)	Standard Consent	Significantly Improved	Higher	Effective in low-literacy groups.

Table 2: Impact on Operational Metrics and User Engagement

Metric	Digital/Multimedia Approach	Traditional Paper Approach	Supporting Evidence
Comprehension & Recall	Improved comprehension and recall scores in studies.	Participants often recall <50% of critical information.	[47] [12]
Enrollment Speed	Up to 40% faster study startup.	Slower, manual processes.	[49]
Documentation Quality	Error rates <2%; automated audit trails.	Manual transcription error rates of 15-20%.	[49] [47]
Participant Engagement	23% higher comprehension; 31% faster enrollment; deeper engagement.	Lower engagement and comprehension scores.	[49]
Format Preference	Varies by demographic (e.g., minors prefer videos; adults prefer text/infographics).	Single, text-heavy format.	[12]

The Researcher's Toolkit: Key Reagents and Digital Solutions

Implementing a rigorous study on digital consent requires a suite of methodological and technological tools. The following table details key "research reagent solutions" essential for this field.

Table 3: Essential Research Reagents and Digital Solutions for eConsent Studies

Item Name	Type/Category	Primary Function in Research
Adapted QuIC Questionnaire	Assessment Tool	A validated instrument adapted for specific populations (e.g., minors, pregnant women) to quantitatively measure objective and subjective comprehension of consent information [12].
Cocreation & Design Thinking Framework	Methodological Protocol	A participatory approach involving potential end-users in the design of eConsent materials to ensure cultural relevance, accessibility, and engagement, thereby improving comprehension outcomes [12].
Multimodal Content Delivery Platform	Digital Platform	A system capable of delivering consent information in multiple formats (layered web text, narrative videos, infographics, printable documents) to cater to diverse learning styles and preferences [12] [50].
eConsent Platform with Analytics	Software System	A secure digital platform that facilitates remote consent, identity verification, comprehension checks, and captures detailed audit trails of user interaction for process analysis [51].
Readability Analysis Software	Analytical Tool	Software (e.g., Readability Studio) used to quantitatively assess the grade-level readability of consent forms, ensuring they meet recommended standards (e.g., 6th-8th grade level) [44].

Logical Framework for Digital Consent Implementation

The decision to implement a digital consent strategy and select the appropriate platform involves evaluating several interconnected factors, from participant demographics to technical infrastructure. The diagram below outlines the logical decision-making workflow and key considerations.

The body of evidence demonstrates that digital and multimedia approaches to informed consent consistently outperform traditional paper-based methods in key metrics of comprehension, satisfaction, and operational efficiency. The synthesis of quantitative data reveals that eConsent platforms, particularly those developed through participatory design and offering multimodal content, can achieve objectively measured comprehension scores exceeding 80% and satisfaction rates above 90% across diverse populations, including minors, pregnant women, and adults in multinational settings [47] [12].

Future research in measuring informed consent comprehension outcomes should focus on longitudinal studies to assess knowledge retention, further explore the surprising finding that prior trial participation may correlate with lower comprehension, and develop more adaptive systems that can dynamically respond to user needs in real-time [47] [12]. The ultimate goal remains the ethical imperative of ensuring true participant understanding, and the data clearly indicates that digital and multimedia tools are powerful assets in achieving this end.

Overcoming Comprehension Barriers: Strategies for Diverse Populations

Addressing Health Literacy Challenges Through Plain Language and Simplification

Health literacy, defined as the skills required to "obtain, process, and understand basic health information and services needed to make appropriate health decisions," represents a critical yet often overlooked component of effective healthcare delivery [52]. With nearly 90% of adults in the United States facing health literacy challenges, the communication gap between medical professionals and patients has substantial implications for patient outcomes, healthcare costs, and overall treatment adherence [53]. This challenge is particularly acute in the context of informed consent processes, where comprehension of complex clinical information directly impacts participant autonomy and decision-making quality in research settings.

The economic burden of inadequate health literacy is staggering, estimated to add $106-238 billion in costs to the healthcare system, representing 7-17% of all personal healthcare expenditures [54]. Beyond financial implications, patients with inadequate health literacy experience poorer health outcomes, including increased emergency department utilization, higher hospitalization rates, and reduced adherence to treatment plans [54]. This comparison guide evaluates experimental approaches to addressing health literacy challenges through plain language and simplification strategies, with particular focus on measuring comprehension outcomes in informed consent processes relevant to pharmaceutical development and clinical research.

Experimental Approaches and Comparative Performance Data

Telehealth vs. In-Person Informed Consent Delivery

A 2025 randomized controlled trial directly compared the effectiveness of teleconsent versus traditional in-person informed consent processes [20]. The study employed a rigorous methodology, randomly assigning 64 participants to either teleconsent (using Doxy.me software) or in-person consent groups. Comprehension was assessed using the validated Quality of Informed Consent (QuIC) questionnaire, while the Decision-Making Control Instrument (DMCI) measured perceived voluntariness, trust, and decision self-efficacy.

Table 1: Comprehension Outcomes - Telehealth vs. In-Person Consent

Metric	Teleconsent Group	In-Person Group	P-value
QuIC Part A Score (Mean)	83.7 (SD 12.3)	85.2 (SD 10.8)	0.29
QuIC Part B Score (Mean)	79.4 (SD 11.6)	81.1 (SD 9.7)	0.25
DMCI Score (Mean)	88.5 (SD 8.3)	87.2 (SD 7.9)	0.38
Health Literacy (SAHL-E)	16.72 (SD 1.88)	17.38 (SD 0.95)	0.03

The results demonstrated no significant differences in comprehension scores between teleconsent and in-person groups, suggesting that telehealth platforms can achieve equivalent understanding while overcoming geographic and accessibility barriers [20]. This has important implications for decentralized clinical trials and research recruitment strategies.

Digital Informed Consent Comprehension Across Populations

A 2025 multinational cross-sectional study evaluated electronic informed consent (eIC) materials developed following i-CONSENT guidelines across diverse populations [12]. The study recruited 1,757 participants across three groups: minors (620), pregnant women (312), and adults (825). Materials were presented through a digital platform offering layered web content, narrative videos, printable documents, and infographics, with comprehension assessed using adapted QuIC questionnaires.

Table 2: Comprehension Outcomes by Population - Digital Informed Consent

Population	Sample Size	Objective Comprehension (%)	Adequate Comprehension (≥80%)	Preferred Format
Minors	620	83.3 (SD 13.5)	76.4%	Video (61.6%)
Pregnant Women	312	82.2 (SD 11.0)	71.8%	Video (48.7%)
Adults	825	84.8 (SD 10.8)	82.3%	Text (54.8%)
Overall	1,757	83.7 (SD 11.9)	77.6%	Varied

The findings revealed several key patterns: generational differences in format preferences, with younger participants favoring video content and older adults preferring textual information; gender effects, with women/girls outperforming men/boys (β=+.16 to +.36); and surprising prior experience effects, where previous trial participation was associated with lower comprehension scores (β=-.47 to -1.77) [12]. The overall high comprehension rates across all groups demonstrate the effectiveness of digitally-delivered, multimodal consent materials.

Health Literacy and Healthcare Utilization Outcomes

A 2022 multicenter cohort study examined the correlation between health literacy levels and subsequent healthcare utilization [54]. Researchers recruited patients admitted to general internal medicine units, measuring health literacy using the full-length Test of Functional Health Literacy in Adults (TOFHLA). Patients were prospectively followed for 90 days post-discharge to track emergency department visits and hospital readmissions.

Table 3: Health Literacy Levels and Healthcare Utilization (N=174)

Health Literacy Level	Percentage of Patients	ED Revisit Rate	Adjusted Odds Ratio for ED Revisit
Adequate	50%	12%	Reference
Marginal	18%	18%	1.8 (0.8-4.1)
Inadequate	32%	26%	3.0 (1.3-6.9)

The study revealed that only half of hospitalized patients had adequate health literacy, with 32% exhibiting inadequate health literacy [54]. Most notably, patients with inadequate health literacy had a threefold increased odds of emergency department revisits compared to those with adequate health literacy, even after controlling for education level and comorbidities. A surprising interaction effect emerged: patients with inadequate health literacy but high education levels demonstrated the highest probability of ED revisits (0.57 ± 0.18) [54].

Experimental Protocols and Methodologies

Protocol 1: Randomized Comparison of Consent Modalities

The telehealth versus in-person consent study employed a randomized comparative design with specific methodological approaches [20]:

• Recruitment: Used an institutional web-based platform to identify interested individuals, followed by eligibility screening and demographic data collection
• Randomization: 1:1 allocation to teleconsent (Doxy.me software) or in-person consent groups
• Assessment Tools:
  • Quality of Informed Consent (QuIC) - measuring comprehension level
  • Decision-Making Control Instrument (DMCI) - assessing perceived voluntariness, trust, and decision self-efficacy
  • Short Assessment of Health Literacy-English (SAHL-E) - measuring baseline health literacy
• Procedure: Both groups reviewed identical consent content with real-time researcher interaction, with electronic signature capture for teleconsent group
• Analysis: Independent t-tests for between-group comparisons, with subgroup analyses by age, sex, and ethnicity

Protocol 2: Multicountry eIC Comprehension Assessment

The digital informed consent study implemented a cross-sectional evaluation across three countries [12]:

• Material Development:
  • Cocreation process using design thinking sessions with minors and pregnant women
  • Online surveys with adults to identify preferences
  • Multidisciplinary team including physicians, epidemiologists, sociologists, and journalists
• Formats Tested:
  • Layered web content with expandable sections
  • Narrative videos (storytelling for minors, question-and-answer for pregnant women)
  • Printable documents with integrated images
  • Customized infographics for complex topics
• Translation Protocol: Professional translation with independent review, emphasizing contextual appropriateness and local adaptation
• Comprehension Assessment: Adapted QuIC questionnaires tailored to each population, with objective comprehension categorized as low (<70%), moderate (70-80%), adequate (80-90%), or high (≥90%)
• Statistical Analysis: Multivariable regression models to identify predictors of comprehension, with satisfaction measured via Likert scales (≥80% considered acceptable)

Visualizing the Plain Language Implementation Framework

The following diagram illustrates the key components and relationships in implementing plain language strategies for health literacy challenges:

Diagram 1: Plain Language Implementation Framework for Health Literacy

Table 4: Essential Research Instruments and Resources

Tool/Resource	Function	Application Context
Quality of Informed Consent (QuIC)	Measures objective and subjective comprehension of consent materials	Clinical trial informed consent evaluation [20] [12]
Test of Functional Health Literacy in Adults (TOFHLA)	Assesses numeracy and reading comprehension in healthcare contexts	Patient health literacy assessment in clinical settings [54]
Decision-Making Control Instrument (DMCI)	Evaluates perceived voluntariness, trust, and decision self-efficacy	Informed consent process quality assessment [20]
eHealth Literacy Scale (eHLS)	Measures ability to seek, find, understand, and evaluate health information from electronic sources	Digital health communication studies [55]
i-CONSENT Guidelines	Evidence-based recommendations for tailoring informed consent processes	Developing comprehensible, accessible consent materials [12]
Physician Labeling Rule (PLR) Format	Standardized structure for presenting prescription drug information	Regulatory-compliant drug labeling [56]

The experimental evidence consistently demonstrates that structured simplification approaches and plain language implementation can significantly improve comprehension outcomes across diverse populations and healthcare contexts. The comparative data reveals several key insights for researchers and drug development professionals:

First, digital delivery modalities can achieve comprehension levels equivalent to traditional in-person consent processes while offering advantages in accessibility and scalability [20]. This supports the integration of telehealth platforms into clinical trial recruitment and consent procedures.

Second, multimodal approaches that accommodate different learning preferences and health literacy levels are essential for equitable understanding. The significant variation in format preferences across age groups and populations underscores the importance of offering content in multiple formats [12].

Third, the relationship between education and health literacy is complex, with high educational attainment not necessarily conferring adequate health literacy skills [54]. This highlights the need for universal precautions approaches that assume all patients may struggle with complex health information, regardless of education level.

Finally, the economic implications of addressing health literacy challenges are substantial, with potential reductions in healthcare utilization and costs through improved patient understanding and self-management [54]. For pharmaceutical development professionals, investing in plain language resources and simplified communication strategies represents both an ethical imperative and a strategic opportunity to enhance medication adherence and patient outcomes.

The integration of these evidence-based approaches into informed consent processes and medication communication represents a critical pathway toward more equitable, effective, and ethical healthcare delivery and clinical research.

Informed consent is a cornerstone of ethical clinical research, grounded in the principles of autonomy and comprehension. For research to be truly ethical, potential participants must not only receive information but must understand it. This creates a critical challenge in global drug development: ensuring that informed consent comprehension is equivalent across diverse cultural and linguistic groups. Comprehension equity means that a participant's understanding of a study's risks, benefits, and procedures is not compromised by their primary language, cultural background, or educational level. Achieving this requires moving beyond simple translation to a deeper, more nuanced process of cultural and linguistic adaptation.

Current research and regulatory guidance increasingly emphasize the need for such adapted approaches. The FDA's Patient-Focused Drug Development (PFDD) guidance series, developed under the 21st Century Cures Act, underscores the importance of collecting and incorporating comprehensive patient experience data, which includes ensuring that consent materials are understandable and meaningful to all populations [57]. This article objectively compares emerging methodologies—from digital consent platforms to co-creation processes—that aim to achieve this equity, analyzing their experimental outcomes and providing a practical toolkit for researchers.

Comparative Analysis of Adaptation Methodologies

The following section provides a data-driven comparison of two dominant approaches for enhancing comprehension equity: digital adaptation and participatory co-creation. The tables below summarize the core protocols and quantitative outcomes from recent, rigorous studies.

Table 1: Experimental Protocols & Methodologies in Consent Comprehension Research

Study & Design	Adaptation Methodology	Population & Sample Size	Primary Comprehension Metrics
Khairat et al. (2025) [20]Randomized Controlled Trial	Digital Adaptation: Telehealth consent ("teleconsent") via Doxy.me software versus traditional in-person consent.	N=64 adults- 32 Teleconsent- 32 In-PersonDiverse in age, sex, and ethnicity [20]	- Quality of Informed Consent (QuIC): Objective understanding (Part A) and subjective understanding (Part B).- Decision-Making Control Instrument (DMCI): Perceived voluntariness, trust, and self-efficacy.
Fons-Martinez et al. (2025) [12]Multicountry Cross-Sectional Study	Participatory Co-Creation: eIC materials developed using i-CONSENT guidelines via design thinking sessions and surveys. Materials included layered web content, narrative videos, and infographics.	N=1757 total- 620 Minors (12-13)- 312 Pregnant Women- 825 AdultsAcross Spain, UK, and Romania [12]	- Adapted QuIC questionnaires tailored for each population.- Satisfaction rates and format preference.

Table 2: Quantitative Comprehension and Satisfaction Outcomes

Study & Groups	Objective Comprehension Score (QuIC Part A)	Subjective Comprehension & Satisfaction	Key Moderating Factors
Khairat et al. (Teleconsent) [20]	No significant difference from in-person group. (Average scores not significantly different, P=.29) [20]	No significant difference in DMCI scores from in-person group (P=.38) [20]	No significant differences found based on age, sex, or ethnicity [20].
Fons-Martinez et al. (All Groups) [12]	- Minors: Mean 83.3% (SD 13.5)- Pregnant Women: Mean 82.2% (SD 11.0)- Adults: Mean 84.8% (SD 10.8) [12]	Satisfaction rates exceeded 90% across all groups.- Minors & Pregnant Women: Preferred video formats.- Adults: Preferred text-based formats [12].	- Women/Girls outperformed men/boys.- Prior trial participation was associated with lower comprehension.- Lower educational levels in Romania linked to lower scores [12].

Detailed Experimental Protocols

To ensure reproducibility and critical appraisal, this section details the experimental workflows and methodologies from the key studies cited.

Protocol 1: Randomized Comparison of Telehealth vs. In-Person Consent

The 2025 randomized controlled trial by Khairat et al. was designed to test the non-inferiority of teleconsent against the gold standard of in-person consent [20].

• Recruitment & Randomization: Potential participants for a parent study on patient portals were identified via an institutional platform. After eligibility screening and demographic data collection, 64 participants were randomly assigned to either the teleconsent group (n=32) or the in-person consent group (n=32) [20].
• Intervention (Teleconsent Group): The teleconsent group used the Doxy.me telehealth platform to interact in real-time with researchers. They reviewed the consent form collaboratively via screen sharing and provided consent using an electronic signature [20].
• Control (In-Person Group): The control group underwent a traditional, face-to-face consent meeting with a researcher [20].
• Outcome Measurement: Immediately following the consent process, all participants completed the validated Quality of Informed Consent (QuIC) survey to measure objective and subjective comprehension, and the Decision-Making Control Instrument (DMCI) to assess perceived voluntariness and decision self-efficacy. Health literacy was also measured using the Short Assessment of Health Literacy-English (SAHL-E) tool [20].
• Analysis: Statistical analyses (including t-tests) were conducted to compare the average QuIC and DMCI scores between the two groups and across demographic subgroups [20].

Protocol 2: Multicountry Evaluation of Co-Created Electronic Consent

The 2025 cross-sectional study by Fons-Martinez et al. evaluated the effectiveness of electronically delivered, co-created consent materials across three European countries [12].

• Material Development (Co-Creation): A multidisciplinary team developed the initial materials in Spanish. This process involved:
  • Design Thinking Sessions: Minors and pregnant women participated in guided sessions to provide direct input on material design, content, and presentation.
  • Online Surveys: Adults provided feedback via surveys to inform material development. The outputs were eIC materials in multiple formats: a layered website, narrative videos, printable documents, and custom infographics [12].
• Cultural and Linguistic Adaptation: The original Spanish materials were professionally translated into English and Romanian. The process prioritized conceptual and cultural equivalence over literal translation, adapting content to local customs and linguistic conventions [12].
• Testing and Data Collection: Participants from Spain, the UK, and Romania were recruited and asked to review the eIC materials for a mock vaccine trial. They could self-select their preferred format(s). After review, they completed a demographic survey and a version of the QuIC questionnaire that had been specifically adapted and validated for their population group (minors, pregnant women, or adults) [12].
• Analysis: Comprehension scores were calculated and categorized (low, moderate, adequate, high). Multivariable regression models were used to identify demographic and experiential predictors of comprehension. Satisfaction and format preferences were analyzed descriptively [12].

Visualizing Workflows for Equity in Consent

The diagram below illustrates the core workflow for developing and implementing culturally and linguistically adapted consent materials, as demonstrated by successful multicountry studies.

The Researcher's Toolkit: Essential Reagents for Equity-Focused Consent Research

Implementing and measuring equity in consent comprehension requires specific methodological tools. The following table catalogs key instruments and approaches used in the featured research.

Table 3: Essential Research Reagents & Instruments for Consent Comprehension Studies

Tool / Reagent Name	Primary Function & Application	Key Characteristics & Considerations
Quality of Informed Consent (QuIC) Questionnaire [20] [12]	Validated instrument to quantitatively measure a participant's objective and subjective understanding of the consent information.	Can be adapted for specific studies and populations. Provides a reliable score for cross-group comparison [20] [12].
Decision-Making Control Instrument (DMCI) [20]	Assesses the participant's perception of the consent process's voluntariness, their trust in the research team, and their confidence in decision-making.	Measures qualitative aspects of consent beyond pure comprehension, crucial for ethical assessment [20].
Co-Creation Frameworks (e.g., Design Thinking) [12]	Participatory methodology to involve the target population directly in the design of consent materials.	Ensures materials are relevant, accessible, and engaging. Particularly critical for vulnerable groups like minors and pregnant women [12].
Multimodal Consent Formats (Layered Web, Video, Infographics) [12]	Provides multiple pathways for participants to access and understand information based on personal preference and literacy.	Video is often preferred by younger and vulnerable populations, while adults may favor text. Offering choice is key to accessibility [12].
Cultural Adaptation Protocol [58]	A structured process beyond literal translation, involving plain language adjustment, cultural contextualization, and back-translation.	Prevents increased text complexity in translation and ensures cultural relevance, addressing critical health literacy disparities [58].

The experimental data clearly demonstrates that both digital adaptation and participatory co-creation are viable methodologies for achieving equity in informed consent comprehension. The teleconsent model offers a practical solution for overcoming geographic and accessibility barriers without compromising understanding [20]. Meanwhile, the co-creation and multimodal approach achieves high comprehension and satisfaction across diverse and vulnerable populations, proving its scalability for multinational trials [12].

A critical finding is that a one-size-fits-all approach is inadequate. Format preferences vary significantly by demographic, and prior trial experience can unexpectedly hinder comprehension, suggesting a need for tailored engagement for returning participants [12]. Furthermore, as emphasized by the National Academy of Medicine, achieving true equity requires moving "beyond translation" to a comprehensive standard that includes plain language and cultural adaptation, followed by field testing with the intended audience [58].

In conclusion, ensuring equity in comprehension is a measurable and achievable goal in clinical research. By adopting the detailed protocols, visualization workflows, and research tools outlined in this guide, drug development professionals can systematically enhance their informed consent processes. This not only strengthens the ethical integrity of clinical trials but also helps build the inclusive and trustworthy research ecosystem necessary for advancing public health.

{# The Role of Teach-Back Methods and Extended Discussions in Reinforcing Understanding

Within clinical research, ensuring genuine comprehension during the informed consent process is a critical ethical and practical challenge. The "therapeutic misconception," where participants do not fully grasp that research participation differs from routine therapeutic care, remains a significant barrier [59]. Two structured communication techniques—the Teach-Back Method and Extended Discussions—are recommended to reinforce understanding, confirm comprehension, and support autonomous decision-making. This guide objectively compares these two approaches within the context of measuring informed consent comprehension outcomes, providing researchers and drug development professionals with experimental data, implementation protocols, and practical toolkits.

Experimental Data and Outcomes Comparison

The effectiveness of the Teach-Back Method and Extended Discussions is supported by empirical studies across various clinical settings. The table below summarizes key quantitative findings from controlled trials and systematic reviews.

Method	Study Design & Population	Key Outcome Measures	Results & Effect Size
Teach-Back Method	RCT: Patients undergoing lumbar disc herniation surgery (n=64) [60]	Discharge Readiness (Scale: 0-10 sub-scores); Discharge Knowledge (Test: 0-20); Satisfaction (Scale: 21-105)	Intervention Group (Teach-Back): Significantly higher scores (p<0.05) on all readiness subscales (personal status, knowledge, coping), knowledge test, and overall satisfaction vs. control.
	Systematic Review (20 studies) [61] [62]	Patient knowledge recall and retention; Hospital re-admission rates; Health-related quality of life	Effective in 19 of 20 studies. Improved learning-related outcomes and objective health outcomes like reduced re-admissions.
	RCT in Emergency Department [63]	Patient comprehension of diagnosis, follow-up, medications, and return symptoms.	Significantly higher knowledge scores for diagnosis (p<0.001), follow-up (p=0.03), and return symptoms (p<0.001). Medication comprehension was higher but not statistically significant (p=0.14).
Extended Discussion	Cochrane Review Protocol (Informed Consent for Clinical Trials) [59]	Understanding of trial rationale and elements (e.g., randomization, right to withdraw); Willingness to participate; Anxiety levels.	Aims to reduce "therapeutic misconception" and improve recall of information. Proposed analysis on understanding based on age and education level.

Detailed Experimental Protocols

Protocol 1: Teach-Back Method for Discharge Education

A 2025 randomized controlled trial exemplifies a rigorous protocol for implementing and evaluating the Teach-Back Method [60].

• 1. Objective: To examine the effect of discharge training based on the teach-back method on discharge readiness and satisfaction in patients undergoing lumbar disc herniation surgery.
• 2. Study Design: A pre-test–post-test RCT following CONSORT 2010 guidelines.
• 3. Participants:
  • Population: Patients aged 18+ undergoing elective microdiscectomy surgery.
  • Sample Size: 64 patients, randomly allocated to an intervention group (n=32) or a control group (n=32).
• 4. Intervention Group Procedure:
  • Step 1 - Education: A healthcare professional provides discharge education verbally.
  • Step 2 - Comprehension Check: The patient is asked to explain the received information in their own words.
  • Step 3 - Clarification: If any misunderstandings are identified, the professional clarifies and re-teaches the information.
  • Step 4 - Re-check: Steps 2 and 3 are repeated until the patient can correctly recall all information [60] [61].
• 5. Control Group Procedure: Receives standard discharge training without the structured teach-back component.
• 6. Outcome Measures:
  • Primary: Readiness for Hospital Discharge Scale (personal status, knowledge, coping ability); Discharge Training Satisfaction Scale.
  • Secondary: Discharge Education Knowledge Test (20-item questionnaire) [60].

Protocol 2: Extended Discussion for Informed Consent

A Cochrane review protocol defines the methodology for applying Extended Discussion in a clinical trial consent context [59].

• 1. Objective: To assess the effects of 'extended discussion' compared with conventional methods on understanding and willingness to participate in clinical trials.
• 2. Study Design: Analysis of randomized and quasi-randomized controlled trials.
• 3. Participants: Potential participants being recruited for clinical trials.
• 4. Intervention Procedure:
  • Step 1 - Two-Way Communication: The process is based on a two-way oral communication between the information-provider (e.g., a consent educator) and the potential participant.
  • Step 2 - Incorporate Values: The discussion is designed to allow participants to seriously consider their own values and beliefs, facilitating reflection on what matters to them.
  • Step 3 - Assess Understanding: The research team asks questions to assess the participant's understanding and address doubts early [59].
• 5. Comparator Procedure: Conventional informed consent process, which may involve providing a document and a brief oral explanation in a single encounter.
• 6. Outcome Measures: Understanding of trial elements; Willingness to participate; Levels of anxiety [59].

Visualization of Workflows

Teach-Back Method Workflow

Extended Discussion Workflow

The Scientist's Toolkit: Key Reagents and Materials

This table details essential materials for implementing and studying these communication methods in a research setting.

Tool / Material	Function in Research Context	Example Application / Notes
Readiness for Hospital Discharge Scale	Validated instrument to quantitatively measure a patient's preparedness to leave the hospital across multiple dimensions [60].	Used as a primary outcome measure in teach-back interventions to quantify impact on perceived personal status, knowledge, and coping ability [60].
Discharge Education Knowledge Test	A customized questionnaire (e.g., 20 right/wrong questions) to objectively assess retention of specific educational content provided during the intervention [60].	Serves as a secondary outcome to evaluate the direct effect of the teach-back method on knowledge retention versus standard care.
Participant Information Sheet	The standard document providing all relevant information about the clinical trial, as required by ethics committees and good clinical practice (GCP) [59].	Forms the basis for the "Extended Discussion" intervention, which uses two-way communication to explain and clarify its contents.
Teach-Back Training Module	An evidence-based, often interactive, online educational toolkit for training healthcare professionals on the correct integration of teach-back into practice [64].	Critical for implementation fidelity. Often includes demonstration videos and self-assessment questions to ensure clinician competence [64].
Consent Form	The document participants sign to indicate their voluntary agreement to participate after understanding the research [59].	The ultimate endpoint for both methods; the quality of understanding preceding signature is the target for improvement.

Both the Teach-Back Method and Extended Discussions offer structured, evidence-based approaches to improving comprehension in the informed consent process. Current evidence, particularly for Teach-Back, shows more consistent quantitative support for improving patient knowledge, self-efficacy, and adherence to health behaviors [61] [65]. Extended Discussion addresses the core challenge of therapeutic misconception in clinical trials by fostering a deeper, values-based dialogue [59].

For researchers, the choice of method may depend on the context: Teach-Back is highly effective for confirming understanding of specific, directive information (e.g., discharge instructions, medication management), while Extended Discussion may be more suitable for complex, value-laden decisions like clinical trial participation. Implementing these techniques with fidelity requires dedicated training for staff and the use of validated assessment tools to measure comprehension outcomes rigorously [64]. As the field advances, future research should focus on long-term knowledge retention and standardized implementation strategies to integrate these powerful tools into routine clinical research practice.

Informed consent represents a cornerstone of ethical clinical research, ensuring respect for participant autonomy through processes that are voluntary, comprehending, and free from undue influence [66]. However, two significant challenges persistently undermine these ideals: therapeutic misconception (TM), where research participants conflate the goals of research (generating generalizable knowledge) with those of clinical care (personalized therapeutic benefit), and undue influence, where external factors compromise the voluntary nature of participation [66] [67]. Current regulatory evolution, including recently proposed FDA guidance that harmonizes with OHRP requirements on "key information" presentation in consent forms, highlights the growing emphasis on ensuring genuine participant understanding [68]. This guide examines experimental approaches for measuring and improving consent comprehension outcomes, providing researchers with evidence-based methodologies to navigate these complex ethical challenges.

Quantitative Evidence: Documenting the Scope and Impact

Research consistently demonstrates concerning patterns in how participants perceive research risks and benefits. The following table summarizes key quantitative findings across multiple studies:

Table 1: Quantitative Evidence on Therapeutic Misconception and Consent Comprehension

Study Population	Sample Size	Key Finding	Metric	Reference/Year
French Oncologists	288	Initial TM knowledge among physicians	16%	PMC (2025) [66]
French Oncologists (after definition)	288	Physicians who encountered TM after education	84%	PMC (2025) [66]
Clinical Trial Participants	155	Unable to report research design risks	73.5%	Social Science & Medicine (2004) [67]
Clinical Trial Participants	155	Reported no risks/disadvantages	23.9%	Social Science & Medicine (2004) [67]
Minors (eIC Comprehension)	620	Mean objective comprehension score	83.3% (SD 13.5)	PMC (2025) [2]
Pregnant Women (eIC Comprehension)	312	Mean objective comprehension score	82.2% (SD 11.0)	PMC (2025) [2]
Adults (eIC Comprehension)	825	Mean objective comprehension score	84.8% (SD 10.8)	PMC (2025) [2]
All eIC Participants	1757	Satisfaction with improved consent materials	>90%	PMC (2025) [2]

Analysis of Quantitative Evidence

The data reveals several critical patterns. First, therapeutic misconception remains prevalent but poorly recognized, even among research professionals. The dramatic increase from 16% to 84% in oncologists recognizing TM after being provided with its definition indicates a fundamental educational gap [66]. Second, participant comprehension gaps are substantial, with early research showing nearly three-quarters of participants unable to identify risks stemming from research design itself [67]. Third, recent interventions show promise, with digital informed consent (eIC) materials achieving comprehension scores exceeding 80% across diverse populations and satisfaction rates over 90% [2].

Experimental Protocols for Measuring Comprehension

The THEMIS Survey Protocol (Oncologist Practices)

• Objective: To evaluate oncologists' knowledge, practices, and ethical concerns regarding therapeutic misconception [66].
• Design: National cross-sectional survey utilizing Likert scales for frequency ("never," "rarely," "sometimes," "often," "systematically") and agreement ("totally disagree" to "totally agree") [66].
• Participants: 288 French oncologists from various specialties recruited over a 7-week period in 2023 [66].
• Key Measures:
  • Initial knowledge of TM concept (dichotomous: yes/no)
  • Estimated frequency of TM encounters after definition provision (10% increments)
  • Practices for preventing/addressing TM during inclusion and throughout protocols
  • Ethical opinions on TM acceptability in different scenarios
• Analysis: Descriptive statistics; chi-square tests for categorical variables; influence of factors like ethics education or research ethics committee participation [66].

Digital Informed Consent (eIC) Evaluation Protocol

• Objective: To assess comprehension and satisfaction with eIC materials developed following i-CONSENT guidelines [2].
• Design: Cross-sectional study with mock clinical trial scenarios across three populations (minors, pregnant women, adults) in Spain, UK, and Romania [2].
• Participants: 1,757 total participants (620 minors, 312 pregnant women, 825 adults) [2].
• Intervention: eIC materials featuring layered web content, narrative videos, printable documents, and infographics, developed through co-creation with target populations [2].
• Key Measures:
  • Objective Comprehension: Adapted Quality of Informed Consent (QuIC) questionnaire with 22 questions scored as low (<70%), moderate (70%-80%), adequate (80%-90%), or high (≥90%) [2].
  • Subjective Comprehension: 5-point Likert scale self-assessment [2].
  • Satisfaction: Usability questions and Likert scales, with scores ≥80% considered acceptable [2].
• Analysis: Multivariable regression models to identify demographic predictors of comprehension; descriptive statistics for satisfaction and format preferences [2].

Therapeutic Misconception Risk Assessment Protocol

• Objective: To evaluate participants' appreciation of risks specific to research design [67].
• Design: Qualitative analysis of intensive interviews with clinical trial participants [67].
• Participants: 155 subjects from 40 different clinical trials at two U.S. medical centers [67].
• Method: Identification and coding of every statement regarding risks or disadvantages of participation into one of five categories:
  • No risks or disadvantages reported
  • Only incidental disadvantages (e.g., travel time)
  • Only disadvantages associated with standard treatment
  • Disadvantages associated with the experimental intervention
  • Risks/disadvantages resulting from research design itself (e.g., randomization, placebos) [67]
• Analysis: Calculation of proportions of participants in each coding category to quantify gaps in understanding of research-specific risks [67].

Visualizing the Therapeutic Misconception Phenomenon

Figure 1: Conceptual Map of Therapeutic Misconception and Undue Influence. This diagram illustrates how participants conflate research and therapeutic contexts, leading to therapeutic misconception, while investigator dual roles create potential for undue influence.

Research Workflow for Consent Comprehension Assessment

Figure 2: Experimental Workflow for Consent Comprehension Research. This workflow outlines a comprehensive approach from co-creation of materials through implementation, assessment, and analysis, emphasizing iterative refinement.

The Scientist's Toolkit: Essential Research Reagents

Table 2: Key Methodological Tools for Informed Consent Comprehension Research

Tool/Reagent	Primary Function	Application Context	Key Features/Components
Quality of Informed Consent (QuIC) Questionnaire	Measures objective understanding of consent information	Pre- and post-consent assessment; intervention evaluation	22 questions with 3 response options ("no," "don't know," "yes"); categorizes comprehension as low, moderate, adequate, or high [2]
THEMIS Survey Instrument	Assesses researcher knowledge/practices regarding TM	Professional practice evaluation; ethics training assessment	Likert scales for frequency and agreement; measures TM encounters, prevention practices, ethical opinions [66]
Structured TM Risk Coding Framework	Qualitative analysis of participant risk appreciation	In-depth interview analysis; comprehension gap identification	5-category coding system: (1) no risks, (2) incidental, (3) standard treatment, (4) experimental intervention, (5) research design [67]
Digital Informed Consent (eIC) Platform	Multimodal consent information delivery	Intervention studies; diverse population engagement	Layered web content, narrative videos, printable documents, infographics; customizable formats [2]
Regression Analysis Models	Identifies predictors of comprehension	Data analysis; subgroup effect identification	Multivariable models examining demographic, experiential, and contextual factors impacting understanding [2]

The quantitative evidence and experimental protocols presented demonstrate both the persistent challenges and promising solutions in mitigating therapeutic misconception and undue influence. Recent innovations, particularly digitally delivered, co-created consent materials presented through multiple formats, show significant promise in improving comprehension scores across diverse populations [2]. The evolving regulatory landscape, including harmonized FDA and OHRP guidance emphasizing "key information" presentation, provides an important framework for implementation [68]. Future research should focus on cultural adaptation of successful interventions, tailored strategies for returning research participants (who demonstrate lower comprehension despite prior experience), and standardized metrics for assessing voluntariness beyond comprehension [2]. By adopting these evidence-based approaches, researchers can more effectively navigate the complex ethical terrain of voluntariness, ultimately strengthening the integrity of the informed consent process.

Evaluating Intervention Efficacy: From Traditional to Technological Solutions

Informed consent (IC) is the ethical and legal cornerstone of clinical research, designed to ensure that participants autonomously agree to partake in a study based on a sufficient understanding of its purpose, procedures, risks, and benefits [69]. Despite its importance, the traditional consent process is widely regarded as flawed. Evidence indicates that an estimated 60% to 70% of individuals do not read or understand the information contained in paper consent forms, and 44% of participants sign without fully grasping the nature of the proposed procedure [70]. Meta-analyses reveal that comprehension of specific trial aspects is particularly poor, with only approximately 52% of participants understanding randomization and 53% grasping placebo usage [69].

The inherent challenges of lengthy, complex forms written above the average patient's literacy level have spurred innovation [69]. This evidence review objectively compares three key approaches to improving the consent process: simplified paper forms, electronic consent (eConsent) platforms, and multimedia tools. The analysis is framed within the critical context of measuring comprehension outcomes, providing researchers and drug development professionals with data-driven insights to enhance ethical research conduct.

Comparing Consent Modalities: Quantitative Outcomes

Robust comparative studies and systematic reviews have quantified the performance of next-generation consent tools against traditional paper-based methods. The table below summarizes key findings across critical outcome domains.

Table 1: Comparative Performance of Consent Approaches Across Key Outcomes

Outcome Domain	Traditional Paper Consent	Simplified Paper Forms	eConsent & Multimedia Tools
Comprehension Objective	Baseline (Often inadequate) [69]	Associated with higher objective and subjective understanding [71]	Significantly better understanding of clinical trial information; 6 out of 10 "high validity" studies reported significantly better comprehension of some concepts [72].
Comprehension Example	~52% understand randomization [69]	Not Specified	Mean objective comprehension scores >80% across diverse populations (minors, pregnant women, adults) [12].
Satisfaction & Acceptability	Baseline	Not Specified	Higher satisfaction and perceived ease of use; rated as more acceptable and usable [70] [72].
Shared Decision Making (SDM)	28% (n=31/109) of patients reported gold-standard SDM [73]	Not Specified	72% (n=82/114) of patients reported gold-standard SDM [73].
Process & Administrative Quality	72% (n=78/109) of forms contained ≥1 error; 63% (n=68/109) omitted core risks [73]	Not Specified	0% (n=0/114) of digital forms contained errors; <2% (n=2/114) omitted core risks [73]. Addresses top regulatory deficiencies (e.g., missing signatures, wrong versions) [72].
Participant Engagement	Lower engagement with content	Not Specified	Greater engagement with content; longer review times potentially reflecting deeper interaction [72].

A 2023 systematic review of 35 studies involving over 13,000 participants concluded that eConsent consistently led to better outcomes, showing significantly better results or no significant difference compared to paper. Critically, none of the studies reported better results with paper than with eConsent [72].

Experimental Protocols and Methodologies

The evidence supporting these comparisons stems from rigorous study designs. The following section details the methodologies of key experiments to provide context for the data.

Randomized Controlled Trial of a Multimedia Digital Tool (VIC)

Objective: To evaluate the feasibility of the Virtual Multimedia Interactive Informed Consent (VIC) tool compared to traditional paper-based methods in an ongoing, real-world biorepository study (GenEx 2.0) [70].

• Trial Design: A randomized controlled trial where participants were allocated to VIC on an iPad (n=25) or standard paper consent (n=25) [70].
• Participants: Recruited from a chest clinic and community; English-speaking, over 21, willing to use an iPad [70].
• Intervention (VIC Tool): The VIC tool was developed using user-centered design and Mayer’s cognitive theory of multimedia learning. It featured:
  • Multimedia Library: Video clips, animations, and presentations to explain risks, benefits, and alternatives.
  • Interactive Features: Automated text-to-speech, virtual coaching, clickable links for more information, and automated quizzes to assess comprehension [70].
• Outcome Measurement: Self-assessed via coordinator-administered questionnaires post-consent, measuring comprehension, satisfaction, perceived ease of use, and perceived time [70].

Multicountry Cross-Sectional Evaluation of eConsent Guidelines

Objective: To assess the comprehension and satisfaction with eIC materials developed following the i-CONSENT guidelines across three distinct populations in Spain, the UK, and Romania [12].

• Study Design: A cross-sectional study with 1,757 participants (620 minors, 312 pregnant women, 825 adults) [12].
• Intervention (eIC Materials): Materials were co-designed using participatory methods (e.g., design thinking sessions). For each mock vaccine trial, participants accessed materials via a digital platform offering:
  • Layered Web Content: A modular approach allowing access to additional details.
  • Multiple Formats: Narrative videos, printable documents, and infographics. Participants could choose or combine formats [12].
• Outcome Measurement:
  • Comprehension: Assessed using an adapted Quality of the Informed Consent (QuIC) questionnaire. Objective comprehension (Part A) was categorized as low (<70%) to high (≥90%).
  • Satisfaction: Evaluated using Likert scales and usability questions, with scores ≥80% deemed acceptable [12].

Comparative Study of Digital vs. Paper Consent in Orthopaedic Surgery

Objective: To compare the quality of consent documentation and patient-reported shared decision-making (SDM) between a digital consent process and a paper-based process [73].

• Study Design: A multi-site, single-centre study of 223 patients in a trauma and orthopaedic department [73].
• Intervention (Digital Consent Platform): Use of the Concentric digital consent platform versus standard paper forms [73].
• Outcome Measurement:
  • Quality of Documentation: Consent forms were assessed for errors of legibility, completion, and accuracy. A Delphi round of experts pre-defined core risks for operations, and forms were analyzed for omissions.
  • Shared Decision Making: Measured using the ‘collaboRATE Top Score’, a validated patient-reported measure for gold-standard SDM [73].

The Scientist's Toolkit: Key Reagents and Materials

The following table details essential digital and methodological "reagents" required for conducting modern informed consent research and implementation.

Table 2: Essential Research Reagents for Digital Consent Investigation

Reagent / Tool Name	Type	Primary Function in Research
Multimedia eConsent Platform	Software	Core intervention for delivering interactive consent information via videos, quizzes, and layered text [70] [74].
Validated Comprehension Questionnaire	Assessment Tool	Measures objective and subjective understanding of consent information; e.g., adapted Quality of Informed Consent (QuIC) [12].
Shared Decision Making (SDM) Measure	Assessment Tool	Quantifies patient involvement in the consent decision; e.g., 'collaboRATE Top Score' [73].
Digital Signature & Audit Trail System	Software Feature	Ensures regulatory compliance (21 CFR Part 11, ICH-GCP) by securely capturing signatures and logging all user interactions [51] [75].
Layered Information Format	Methodological Framework	Allows presentation of key information first with optional drill-down details, improving clarity and accommodating different information preferences [12].

Visualizing the Digital Consent Comprehension Workflow

The effectiveness of eConsent tools can be understood as a structured workflow that leverages multimedia learning principles to enhance cognitive processing. The diagram below illustrates this pathway from information delivery to comprehension outcome assessment.

Digital Consent Comprehension Pathway: This diagram illustrates the enhanced cognitive pathway enabled by multimedia eConsent tools. Information is delivered through dual channels (visual and auditory), aligning with Mayer's cognitive theory of multimedia learning [70]. This is followed by active learning components that encourage engagement, leading to better knowledge integration and reliable comprehension assessment, ultimately resulting in a more informed decision.

Discussion and Future Directions

The evidence demonstrates that eConsent and multimedia tools consistently outperform traditional paper consent by enhancing participant comprehension, satisfaction, and the administrative quality of the process. Simplified forms show promise, but digital tools offer a more robust, scalable, and engaging solution [71] [72]. A crucial finding for global research is that while co-created materials can be effective across countries, cultural adaptation remains essential for optimizing comprehension, as evidenced by lower scores in certain subgroups within multinational studies [12].

Future research should focus on standardizing comprehension metrics, exploring the impact of artificial intelligence in personalizing consent information, and validating these tools in broader cultural and low-literacy contexts. The integration of eConsent into a broader digital ecosystem—including Electronic Health Records (EHRs) and electronic Clinical Outcome Assessments (eCOAs)—positions it not merely as a digital form, but as the digital foundation for participant-centric clinical trials [51] [74]. For researchers, adopting these evidence-backed tools is a critical step toward fulfilling the ethical imperative of truly informed consent.

Informed consent is a cornerstone of ethical clinical research, ensuring that participants autonomously agree to partake in a study based on a clear understanding of its elements. However, the traditional model—often characterized by lengthy, complex paper documents—faces significant challenges in achieving this goal. Comprehension gaps are widespread, and administrative burdens are substantial [72]. This comparison guide objectively evaluates the performance of emerging consent methodologies against traditional standards, focusing on comprehension outcomes, participant satisfaction, and documentation quality. The analysis is framed within a broader thesis on measuring informed consent comprehension outcomes, providing drug development professionals and clinical researchers with evidence-based insights for protocol design.

The evolution of consent models is driven by the need to overcome the limitations of paper-based processes. The U.S. Food and Drug Administration (FDA) notes that traditional informed consent documents are often "long, complex, and legalistic," failing to leverage modern innovations that could facilitate understanding [76]. This guide systematically compares traditional in-person consent, streamlined paper consent, and digital eConsent solutions to determine which approaches most effectively achieve the dual objectives of ethical understanding and operational excellence.

Tabular Comparison of Consent Modalities

The following table summarizes key performance metrics across the primary consent modalities, synthesizing data from recent comparative studies.

Table 1: Comparative Outcomes of Consent Modalities

Consent Modality	Average Comprehension Score	Participant Satisfaction	Key Advantages	Key Limitations
Traditional Paper-Based Consent	Variable; often poor without simplification [23] [72]	Not systematically higher than alternatives [72]	Familiarity; no technology requirement	Often exceeds recommended readability levels [44]; administrative burdens [72]
Streamlined/Concise Paper Consent	Equivalent to standard forms in controlled studies [23]	Higher satisfaction reported in some studies [23]	Improved readability without technology	Requires significant redesign effort; remains static
Telehealth/Video Consent	No significant difference in QuIC scores vs. in-person (P=.29) [20]	High; addresses geographic/access barriers [20]	Overcomes geographic barriers; real-time interaction	Requires reliable technology and internet access
Multimodal Digital Consent (eConsent)	>80% objective comprehension across diverse groups [12]	>90% satisfaction in multinational study [12]	High engagement; layered information; customizable format	Increased cycle time for consent process [72]

Detailed Experimental Protocols and Outcomes

Protocol 1: Randomized Study of Telehealth vs. In-Person Consent

• Objective: To evaluate participant comprehension and decision-making in teleconsent versus traditional in-person informed consent processes [20].
• Study Design: A randomized comparative study with two arms: a teleconsent group using the Doxy.me platform and an in-person consent group.
• Participants: 64 participants recruited for a parent study on patient portals (54 females, 84.4%; 44 aged 18-34, 68.7%) [20].
• Methodology:
  • Intervention: The teleconsent group reviewed and electronically signed consent documents via Doxy.me in real-time interaction with researchers.
  • Assessments:
    • Comprehension: Measured using the Quality of Informed Consent (QuIC) questionnaire, which assesses understanding of consent material.
    • Decision-Making: Evaluated using the Decision-Making Control Instrument (DMCI) survey to gauge perceived voluntariness, trust, and self-efficacy.
    • Health Literacy: Assessed with the Short Assessment of Health Literacy-English (SAHL-E) tool.
• Key Results:
  • No significant differences were found between groups in QuIC Part A (P=.29), QuIC Part B (P=.25), or DMCI scores (P=.38) [20].
  • The mean SAHL-E score was slightly higher in the in-person group (17.38 vs. 16.72, P=.03), but this did not translate to differences in comprehension outcomes.
• Conclusion: Telehealth consent achieved equivalent participant understanding and engagement compared to in-person visits, while offering the advantage of overcoming accessibility barriers [20].

Protocol 2: Assessment of Simplified vs. Standard Paper Consent Forms

• Objective: To evaluate the effect of a shorter, simpler consent form on the comprehension and satisfaction of research participants [23].
• Study Design: A substudy embedded within a phase I bioequivalence trial, randomizing participants by visit date to receive either a standard or concise consent form.
• Participants: Healthy volunteers considering enrollment in an atorvastatin bioequivalence study.
• Methodology:
  • Interventions:
    • Standard Consent Form: 14 pages, 5,716 words, 8.9 Flesch-Kincaid reading level.
    • Concise Consent Form: 4 pages, 2,153 words, 8.0 Flesch-Kincaid reading level. Simplification was achieved by eliminating repetition, removing unnecessary detail, and using plain language [23].
  • Assessment: Participants completed a self-administered 36-item survey immediately after reading the consent form, without referring back to the document. The survey included 15 multiple-choice questions assessing comprehension of core consent elements.
• Key Results:
  • Study volunteers demonstrated the same level of comprehension after reading either the standard or concise consent form, confirming the hypothesis [23].
  • Participants reported higher satisfaction with the concise consent form compared to the standard form.
• Conclusion: Simplifying consent forms through reduced length and improved readability can maintain comprehension while enhancing participant satisfaction, challenging the necessity of excessively detailed documents.

Protocol 3: Multicountry Evaluation of Digital Informed Consent

• Objective: To assess the comprehension and satisfaction of minors, pregnant women, and adults with electronically delivered, guideline-based consent materials across different countries [12].
• Study Design: A cross-sectional study conducted in Spain, the United Kingdom, and Romania.
• Participants: 1,757 total participants (620 minors, 312 pregnant women, and 825 adults) [12].
• Methodology:
  • Intervention: Participants reviewed electronically delivered informed consent (eIC) materials for mock vaccine trials via a digital platform offering multiple formats: layered web content, narrative videos, printable documents, and infographics.
  • Materials Development: Content was co-designed using participatory methods, including design thinking sessions with minors and pregnant women, and online surveys with adults, following i-CONSENT guidelines [12].
  • Assessment:
    • Comprehension: Measured using population-tailored adaptations of the QuIC questionnaire. Objective comprehension (Part A) was categorized as low (<70%), moderate (70%-80%), adequate (80%-90%), or high (≥90%).
    • Satisfaction: Evaluated using Likert scales and usability questions, with scores ≥80% deemed acceptable.
• Key Results:
  • Comprehension: Mean objective comprehension scores exceeded 80% across all groups: minors (83.3), pregnant women (82.2), and adults (84.8) [12].
  • Satisfaction: Rates surpassed 90% in all groups (minors 97.4%, pregnant women 97.1%, adults 97.5%) [12].
  • Format Preference: Minors and pregnant women predominantly preferred video formats (61.6% and 48.7%, respectively), while adults favored text (54.8%).
• Conclusion: eIC materials developed through participatory design and delivered in multiple, flexible formats can achieve high comprehension and satisfaction across diverse populations and cultural contexts.

Visual Workflow of Comparative Consent Research

The following diagram illustrates the generic experimental workflow common to the comparative studies cited in this guide, highlighting parallel processes across different consent modality comparisons.

Figure 1: Generic workflow for comparative consent studies.

The following table catalogues key instruments and solutions used in the featured experiments to assess consent comprehension and quality.

Table 2: Essential Research Reagents and Tools for Consent Comprehension Studies

Tool/Reagent Name	Primary Function	Application in Research
Quality of Informed Consent (QuIC)	Validated questionnaire measuring objective and subjective comprehension of informed consent elements [20] [12].	Serves as a primary endpoint in trials comparing consent modalities; provides quantifiable comprehension scores.
Decision-Making Control Instrument (DMCI)	Survey assessing perceived voluntariness, trust, and decision self-efficacy during consent [20].	Measures psychological aspects of the consent process beyond mere information recall.
Short Assessment of Health Literacy (SAHL)	Tool to objectively measure participants' health literacy levels [20].	Used as a baseline characteristic or covariate to control for health literacy's influence on comprehension outcomes.
Interactive Digital Platforms (e.g., Doxy.me)	Software enabling real-time video interaction and electronic signature capture for remote consent [20].	Facilitates the teleconsent intervention arm in randomized trials; requires internet connectivity.
Multimodal eConsent Materials	Digitally delivered content combining layered text, video, infographics, and interactive quizzes [12] [72].	Serves as the experimental intervention in studies testing enhanced consent formats against static paper documents.
Readability Analysis Software	Programs (e.g., Readability Studio) calculating reading grade level using Flesch-Kincaid and other metrics [23] [44].	Quantifies the complexity of consent documents; ensures they meet recommended grade-level standards (e.g., 6th-8th grade).

Discussion and Integrated Analysis

The body of evidence demonstrates a clear trend: modernized consent approaches perform at least as well as, and often better than, traditional paper-based methods in critical metrics of comprehension and satisfaction. A 2023 systematic review of 35 studies concluded that compared to paper consent, eConsent resulted in a better understanding of clinical trial information, greater engagement with content, and higher ratings for acceptability and usability [72]. None of the reviewed studies found paper consent to be superior [72].

A crucial finding across studies is the importance of process and design over the mere medium of delivery. The success of eConsent is not automatic but depends on the implementation of participant-centered design principles. This includes using plain language, incorporating multimodal elements (video, graphics), and adopting a layered information approach that presents key facts first, with details available on demand [12] [76]. Furthermore, involving patients and the public in the co-creation of consent materials, as done in the i-CONSENT study, significantly enhances their effectiveness and relevance [12].

Regulatory bodies are aligning with this evidence. The FDA encourages the use of a "key fact summary" at the beginning of consent documents and supports the integration of appropriate technological innovations to facilitate understanding [76]. This shift in focus—from a document designed for liability protection to a process designed for participant understanding—represents the most significant evolution in informed consent practice. For researchers and sponsors, this means that investing in well-designed, digital-first consent processes is not only an ethical imperative but also a strategic opportunity to improve trial enrollment, retention, and data quality.

Informed consent (IC) is a cornerstone of ethical clinical research, foundational to ensuring participant autonomy. The process is designed to ensure that potential participants comprehend the study's purpose, procedures, risks, and benefits before deciding to enroll. However, traditional consent processes often rely on complex, static documents that can lead to comprehension gaps and hinder the participant's ability to make a truly informed decision. The emergence of Artificial Intelligence (AI) and Large Language Models (LLMs) presents a transformative opportunity to address these long-standing challenges. This guide explores the latest technological innovations in consent generation, objectively comparing emerging AI-driven approaches with traditional and digital methods. Framed within the critical context of measuring comprehension outcomes, this analysis provides researchers, scientists, and drug development professionals with the data and protocols needed to evaluate these tools for modern, participant-centered clinical trials.

Comparative Analysis: Traditional, Digital, and AI-Enhanced Consent

The following table summarizes the key characteristics and documented performance of different consent methodologies, providing a baseline for comparison.

Table 1: Comparison of Consent Methodologies and Their Measured Outcomes

Methodology	Key Features	Reported Comprehension Rates	Participant Satisfaction	Key Limitations
Traditional Paper-Based Consent [77]	Static text documents, in-person explanation.	Varies widely; studies often show significant gaps. [12]	Not systematically high; impersonal.	Low engagement, "one-size-fits-all," difficult to verify understanding.
Digital Informed Consent (eIC/DC) [12]	Layered web content, videos, infographics; accessible via digital platforms.	Objective Comprehension: Minors: 83.3%; Pregnant Women: 82.2%; Adults: 84.8%. [12]	Exceeded 90% across all participant groups. [12]	Requires cultural adaptation; effectiveness can vary with education level. [12]
AI-Enhanced Consent (Emerging) [78] [79]	Dynamic, personalized content generation; interactive Q&A; automated comprehension assessment.	Data still emerging; potential for high comprehension via personalization.	Potential for high satisfaction via tailored formats and engagement.	Risks of AI "hallucinations," data privacy concerns, and potential for coercive design. [79]

Experimental Protocol for Evaluating Digital Consent Comprehension

The quantitative data presented in Table 1 for digital consent (eIC) originates from a rigorous, multi-country study. The methodology below provides a replicable framework for researchers seeking to evaluate consent tools.

• Study Design: A cross-sectional evaluation was conducted across Spain, the United Kingdom, and Romania. [12]
• Participants: 1,757 participants were enrolled, including 620 minors (aged 12-13), 312 pregnant women, and 825 adults (millennials and Generation X). [12]
• Intervention: Participants reviewed eIC materials for mock vaccine trials via a digital platform. Materials were co-designed with target populations and offered in multiple formats (layered website, narrative videos, infographics, printable documents). [12]
• Assessment Tool: Comprehension was measured using an adapted version of the Quality of the Informed Consent (QuIC) questionnaire. Objective comprehension (Part A) was scored and categorized as low (<70%), moderate (70-80%), adequate (80-90%), or high (≥90%). Subjective comprehension and satisfaction were measured via Likert scales. [12]
• Analysis: Multivariable regression models were applied to identify demographic and experiential predictors of comprehension. [12]

The AI Paradigm: From Automation to Personalization

AI and LLMs are poised to move beyond the static digitalization of consent forms towards a dynamic, adaptive, and deeply personalized process. Their application spans the entire consent lifecycle, as illustrated in the following workflow.

Key Innovations and Experimental Applications

• Intelligent Personalization: AI can tailor consent information by adapting reading levels, leveraging preferred formats (e.g., video, text, audio), and incorporating culturally relevant examples. This addresses the finding from eIC research that format preferences vary significantly—61.6% of minors preferred videos, while 54.8% of adults favored text. [12] AI can automatically serve the optimal format.

• Interactive Comprehension Partner: LLMs can power conversational interfaces that allow potential participants to ask questions in their own words at any time, receiving instant, consistent, and easy-to-understand answers. This mimics the role of a study coordinator, providing on-demand clarification that is crucial for true understanding. [78]

• Automated Comprehension Verification: Replacing simple quizzes, AI can analyze participant interactions and responses to infer comprehension levels, flagging topics that are not well understood for further review by a human professional. This creates a data-driven feedback loop to ensure understanding is achieved before consent is finalized. [78]

The Researcher's Toolkit: Essential Components for AI-Driven Consent

Implementing and studying AI-enhanced consent requires a suite of technological and methodological components.

Table 2: Research Reagent Solutions for AI-Enhanced Consent Studies

Tool Category	Function	Example Applications / Notes
Large Language Models (LLMs)	Generate and simplify text; power conversational Q&A.	Models like GPT-4, Claude, or specialized medical LLMs. Must be fine-tuned for medical and regulatory terminology. [78] [80]
Multimodal AI Platforms	Generate and understand text, images, and audio for accessible content.	Crucial for creating narrative videos and infographics, which boost comprehension in minors and low-literacy populations. [12] [81]
Behavioral Analytics Engines	Track user engagement (time spent, clicks, replay of sections) to infer comprehension.	Provides objective data on which parts of the consent form are most confusing. [82]
Adaptive Consent Platforms	The digital framework that integrates AI models and delivers the experience to participants.	Platforms must comply with data security standards (e.g., HIPAA, GDPR) and be compatible with clinical trial management systems. [12] [79]
Comprehension Assessment Tools	Validated questionnaires to objectively measure understanding as a study outcome.	The Quality of Informed Consent (QuIC) questionnaire is a key example; requires adaptation for specific studies. [12]

Experimental Framework for Evaluating AI-Generated Consent

To validate the efficacy of AI-generated consent, researchers can employ the following experimental protocol, which builds upon established eIC evaluation methods.

Detailed Experimental Methodology

• Hypothesis: AI-generated, personalized consent forms will yield significantly higher objective comprehension scores and participant satisfaction compared to standard consent forms.

• Study Design: A randomized controlled trial (RCT) is the gold standard for this evaluation.

• Participants: Recruit a diverse cohort reflective of intended trial populations (varying in age, health literacy, education, and cultural background). Randomly assign participants to either the intervention (AI-generated consent) or control (standard consent) group. [12]

• Intervention Group Protocol:

  • Initial Profiling: Participants complete a brief survey on their preferred learning style (text, video, audio) and demographic background.
  • AI-Generation: An LLM processes the study protocol and, based on the participant's profile, generates a tailored consent document. This may involve simplifying language, inserting relevant infographics, or generating a short summary video.
  • Interactive Session: The participant reviews the AI-generated materials. An LLM-powered chatbot is available for real-time Q&A. All interactions are logged.

• Control Group Protocol: Participants review a standard, non-personalized electronic or paper consent form developed according to current best practices.

• Outcome Measures:

  • Primary Outcome: Objective Comprehension Score, measured by a validated instrument like the QuIC immediately after the consent process. [12]
  • Secondary Outcomes:
    • Subjective Comprehension: Participant self-rating of understanding. [12]
    • Satisfaction and Usability: Measured via Likert scales and structured questions. [12]
    • Behavioral Engagement: Metrics such as time spent on sections, number of questions asked to the AI, and replay of video content. [82]

• Statistical Analysis: Compare primary and secondary outcomes between groups using appropriate statistical tests (e.g., t-tests, ANOVA). Use regression models to identify factors (e.g., age, education, AI usage patterns) that predict high comprehension.

Challenges and Ethical Safeguards

While the potential is significant, the integration of AI into the consent process is not without risks that must be meticulously managed.

• Accuracy and "Hallucinations": LLMs can generate plausible but incorrect or fabricated information. Safeguard: Implement a human-in-the-loop review process where a study coordinator validates the AI-generated content before it is presented to participants. Continuous monitoring and fine-tuning on curated datasets are essential. [79]

• Data Privacy and Security: AI systems processing sensitive health information are attractive targets for cyberattacks. Safeguard: Employ robust data encryption, strict access controls, and ensure that AI platforms are fully compliant with regulations like HIPAA. On-premise or private cloud deployments may be preferable. [79]

• Algorithmic Bias: If trained on non-representative data, AI can produce consent materials that are less effective or even misleading for underrepresented populations. Safeguard: Utilize diverse training datasets and conduct subgroup analyses in validation studies to identify and mitigate disparate impacts. [78]

• Erosion of Trust and Human Element: Over-reliance on AI could make the process feel impersonal and undermine the trust built through human interaction. Safeguard: Position AI as a tool to augment, not replace, the research team. Ensure seamless escalation paths to human counselors for complex or sensitive questions. [79]

The evolution from static paper forms to digital consent and now to AI-driven personalization represents a paradigm shift in the pursuit of truly informed consent. Quantitative evidence from digital consent studies demonstrates that participant-centric design can achieve comprehension rates exceeding 80% and satisfaction rates over 90%. [12] AI and LLMs offer the potential to build upon this success by introducing unprecedented levels of personalization, interactivity, and comprehension assurance. For the research community, the path forward involves rigorous, evidence-based validation of these tools using controlled experimental protocols. By proactively addressing the associated ethical and technical challenges, researchers can harness these emerging innovations to not only improve trial efficiency but, more importantly, to deepen participant understanding and uphold the fundamental ethical principle of autonomy in clinical research.

Regulatory Perspectives and Validation Standards for New Consent Approaches

Informed consent is undergoing a profound transformation, moving from static, paper-based processes to dynamic, digital, and participant-centric interactions. For researchers, scientists, and drug development professionals, navigating the evolving regulatory landscape and validating the effectiveness of these new consent approaches is critical for both ethical compliance and scientific integrity. This guide provides a comparative analysis of emerging consent methodologies, framed within the context of measuring comprehension outcomes. It synthesizes current regulatory perspectives from key authorities like the FDA and FCC, examines experimental data on digital tools, and details the protocols needed to validate new consent approaches against traditional standards. The objective is to equip researchers with the knowledge to implement and rigorously evaluate consent processes that truly protect participants and enhance the quality of research.

Current Regulatory Perspectives on Consent

Regulatory bodies are actively updating their guidelines to address the shortcomings of traditional consent and embrace innovative solutions. The perspectives vary across domains, from clinical research to telecommunications.

Table 1: Key Regulatory Perspectives on Consent (2024-2025)

Regulatory Body	Domain	Key Guidance / Update	Core Requirements & Recommendations
U.S. Food and Drug Administration (FDA) [83] [76]	Clinical Research	Finalized guidance on informed consent, emphasizing a concise, participant-centric approach.	🡅 Begin with a "key information" summary to aid decision-making. [76]🡅 Use appropriate innovations (e.g., visuals, technology) to facilitate understanding. [83] [76]🡅 The consent process should be an ongoing, interactive conversation. [76]
Federal Communications Commission (FCC) [84]	Telemarketing/Communications	New "one-to-one consent" rule under the TCPA, effective January 2025.	🡅 Requires explicit, written consent for each communication channel (calls, texts). [84]🡅 Bans reliance on implied consent or broad terms and conditions. [84]🡅 Mandates strict penalties for violations (up to $1,500 per incident). [84]
European General Data Protection Regulation (GDPR) [85] [86]	Data Privacy (EU/UK)	Intensified enforcement in 2025, specifically targeting "dark patterns" in consent interfaces. [86]	🡅 Consent must be freely given, specific, informed, and unambiguous (opt-in). [85]🡅 Granular controls must be offered for different cookie/data categories. [86]🡅 Rejecting consent must be as easy as accepting it. [86]
California Consumer Privacy Act (CPRA) [86]	Data Privacy (U.S. - CA)	Fully enforceable in 2025, with specific requirements for data sharing and consent. [86]	🡅 Primarily an opt-out framework for data processing. [85]🡅 Requires explicit opt-in consent for processing sensitive data. [85]🡅 Websites must support the Global Privacy Control (GPC) signal and provide a clear "Do Not Sell" link. [86]

A critical legal development outside these frameworks is the emergence of laws that threaten the finality of consent. A 2025 perspective in the New England Journal of Medicine highlights a Utah law that allows minors to retroactively withdraw consent for gender-affirming care received as minors [87]. This creates significant legal instability, as clinicians can no longer rely on consent given at the time of care, potentially undermining the foundation of the clinician-patient relationship across all practice areas [87].

Comparative Analysis of New Consent Approaches

This section compares the performance of new consent methodologies against traditional standards, with a focus on quantitative comprehension outcomes.

Digital and Telehealth Consent vs. In-Person Consent

Digital consent (e-consent) uses multimedia, interactive graphics, and digital signatures, while teleconsent conducts the consent process remotely via video platforms.

Table 2: Comprehension and Decision-Making Outcomes: Telehealth vs. In-Person Consent

Metric	Telehealth/Teleconsent Group	In-Person Consent Group	P-value	Conclusion
Study Design [20]	Randomized Controlled Trial (RCT), 32 participants	RCT, 32 participants	-	Direct comparative study
Comprehension (QuIC Part A) [20]	Mean Score at Baseline and Follow-up	Mean Score at Baseline and Follow-up	P = 0.29	No significant difference
Comprehension (QuIC Part B) [20]	Mean Score at Baseline and Follow-up	Mean Score at Baseline and Follow-up	P = 0.25	No significant difference
Decision-Making (DMCI) [20]	Mean Score for perceived voluntariness, trust, self-efficacy	Mean Score for perceived voluntariness, trust, self-efficacy	P = 0.38	No significant difference
Health Literacy (SAHL-E) [20]	Mean: 16.72 (SD 1.88)	Mean: 17.38 (SD 0.95)	P = 0.03	Significant, but scores high in both

Key Findings: The RCT found no statistically significant differences in comprehension or decision-making quality between teleconsent and traditional in-person methods [20]. This demonstrates that teleconsent is a viable alternative that maintains participant understanding and engagement while overcoming geographic and accessibility barriers [20].

E-Consent in Low-Resource Settings

A 2025 systematic review evaluated the role of e-consent in enhancing comprehension and documentation in low-resource settings [47].

Table 3: Effectiveness of E-Consent in Low-Resource Settings

Study / Context	Intervention	Key Outcomes vs. Paper-Based Consent
Ngoliwa et al., 2025 (Malawi) [47]	Tablet-based, offline e-consent	🡅 100% participation rate.🡅 Eliminated documentation errors (vs. 43% error rate in paper forms).
Afolabi et al., 2014 (Nigeria) [47]	Multimedia (audio-visual) consent tool for low-literacy populations	🡅 Significantly improved understanding in low-literacy groups.🡅 Higher participant satisfaction.
Gesualdo et al., 2021 (Systematic Review) [47]	Various multimedia consent approaches	🡅 Consistent gains in comprehension and satisfaction across heterogeneous trial populations.
Overall Synthesis [47]	Multimedia, web-based, and offline e-consent	🡅 Improved comprehension and satisfaction.🡅 Marked decrease in documentation errors.🡅 Effects on enrollment were mixed.

Standardized Consent Platforms for Health Data

A 2025 perspective article proposed a Standard Health Consent (SHC) platform to manage consent for person-generated health data from wearables and apps [88]. This centralised system aims to ensure regulatory compliance and user autonomy through three core components:

• SHC Connect: Integrated into health apps to capture consent.
• SHC Management App: A standalone app or integration for users to control data sharing preferences.
• SHC Service: A backend for storing and processing consent metadata [88].

This model contrasts with opt-out frameworks (like parts of the European Health Data Space) by empowering users with active, granular control, which is argued to be more ethical and sustainable for data sharing [88].

Experimental Protocols for Validating Consent Comprehension

To ensure new consent approaches are effective, their validation must be grounded in rigorous experimental design. Below are detailed protocols for key methodologies cited in this guide.

Protocol 1: Randomized Comparison of Teleconsent vs. In-Person Consent

This protocol is based on the 2025 study by Khairat et al. [20].

• Objective: To evaluate the effectiveness of IC processes through telehealth compared to traditional in-person visits on participant comprehension and decision-making.
• Study Design: Randomized comparative study.
• Participant Recruitment:
  • Identify potential participants via an institutional web-based platform.
  • Contact to assess eligibility and gather demographic data.
  • Randomly assign eligible individuals to either the teleconsent or in-person group.
• Intervention Group (Teleconsent):
  • Use a secure teleconferencing platform (e.g., Doxy.me).
  • The researcher interacts with the participant in real-time to review the consent document.
  • The participant provides consent via an electronic signature.
• Control Group (In-Person Consent):
  • Conduct the consent meeting face-to-face in a clinical setting.
  • Use a standard paper consent form.
  • The participant provides consent with a written signature.
• Outcome Measures & Instruments:
  • Primary Outcome: Comprehension. Measured using the Quality of Informed Consent (QuIC) instrument. The QuIC has two parts: Part A assesses factual understanding, and Part B assesses perceived understanding.
  • Primary Outcome: Decision-Making. Measured using the Decision-Making Control Instrument (DMCI), which assesses perceived voluntariness, trust, and decision self-efficacy.
  • Covariate: Health Literacy. Measured using the Short Assessment of Health Literacy-English (SAHL-E) tool.
  • Assessments are administered at baseline (after the consent process) and at a follow-up visit.
• Data Analysis:
  • Use t-tests or non-parametric tests to compare average QuIC and DMCI scores between the teleconsent and in-person groups.
  • Use subgroup analysis to assess outcomes based on age, sex, and ethnicity.

Protocol 2: Systematic Review of E-Consent in Low-Resource Settings

This protocol is based on the 2025 systematic review published in Cureus [47].

• Objective: To assess the role of digital consent tools in enhancing comprehension, satisfaction, and documentation quality in low-resource settings.
• Search Strategy:
  • Databases: PubMed, Embase, Scopus, and Cochrane Library.
  • Search Terms: Combinations of "digital consent," "e-consent," "electronic informed consent," "low-resource," "developing countries," and "clinical trials."
  • Time Frame: Up to August 2025.
• Eligibility Criteria (PICO):
  • Population (P): Underserved or low-resource populations (adults only).
  • Intervention (I): Digital or electronic informed consent tools (multimedia, web-based, mobile, AI-assisted).
  • Comparator (C): Traditional paper-based informed consent.
  • Outcomes (O): Participation rates, comprehension, satisfaction, retention, documentation quality.
• Study Selection & Data Extraction:
  • Two independent reviewers screen titles/abstracts and then full texts.
  • A standardized data extraction form is used to record study characteristics, demographics, intervention type, and outcomes.
• Risk of Bias Assessment:
  • Non-randomized studies are assessed using ROBINS-I.
  • Systematic reviews are assessed using AMSTAR-2.
• Data Synthesis:
  • A narrative synthesis is performed due to study heterogeneity.
  • Studies are organized by design, and outcomes, barriers, and facilitators are analyzed thematically.

The Scientist's Toolkit: Key Reagents & Materials

Table 4: Essential Research Reagents and Tools for Consent Comprehension Research

Item Name	Type (Software/Instrument)	Primary Function in Consent Research
Doxy.me [20]	Software Platform	A secure, HIPAA-compliant teleconferencing platform used to conduct remote "teleconsent" sessions, enabling real-time interaction and e-signing.
Quality of Informed Consent (QuIC) [20]	Validated Instrument	A survey instrument designed to quantitatively measure a participant's level of comprehension and understanding of the informed consent document.
Decision-Making Control Instrument (DMCI) [20]	Validated Instrument	A survey tool that assesses the participant's perceived voluntariness, trust in the research team, and self-efficacy regarding their decision to participate.
Short Assessment of Health Literacy (SAHL-E) [20]	Validated Instrument	A tool used to measure an individual's health literacy level, which is a critical covariate that can influence consent comprehension outcomes.
Open Data Kit (ODK) [47]	Software Platform	An open-source suite of tools used to build mobile data collection forms, such as those for implementing e-consent on tablets in low-resource settings.
Keycloak [88]	Software System	An open-source identity and access management solution that can be integrated into consent platforms to handle secure user authentication and pseudonymization.

The regulatory and research landscape for informed consent is shifting towards greater participant engagement, digital integration, and empirical validation. For drug development professionals and researchers, this means that simply obtaining a signature is no longer sufficient. The future lies in implementing consent processes that are not only compliant with evolving regulations from the FDA, FCC, and global data protection authorities but are also proven to be effective. As demonstrated by the experimental data, digital tools like teleconsent and e-consent platforms can achieve comprehension outcomes equivalent to or better than traditional methods, while also improving accessibility and documentation accuracy. By adopting the rigorous validation protocols and standardized tools outlined in this guide, the research community can ensure that the principle of informed consent continues to be robustly upheld in an increasingly digital and complex research environment.

Conclusion

Measuring informed consent comprehension is not merely an administrative task but a fundamental ethical requirement for valid clinical research. The evidence consistently reveals significant gaps in participant understanding of core trial concepts, necessitating systematic assessment approaches. Effective strategies combine simplified communication, multimodal delivery including eConsent platforms, and continuous evaluation throughout the research process. Future directions must focus on developing standardized, validated measurement tools adaptable to diverse populations and settings, while embracing technological innovations like AI to create more accessible, understandable consent materials. By prioritizing genuine comprehension, the research community can strengthen ethical practice, enhance participant engagement, and ultimately improve the quality and inclusivity of clinical research.

References

• 1. The Clinical Research Involvement Scales (CRIS) [https://pmc.ncbi.nlm.nih.gov/articles/PMC2892193/]
• 2. Digital Informed Consent/Assent in Clinical Trials Among ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12356628/]
• 3. Reporting Discrepancies between the ClinicalTrials.gov ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC4617780/]
• 4. Best Practices for Developing and Validating Scales ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC6004510/]
• 5. Randomized controlled trials – The what, when, how and why [https://www.sciencedirect.com/science/article/pii/S147751312400617X]
• 6. Randomization in clinical studies - PMC [https://pmc.ncbi.nlm.nih.gov/articles/PMC6547231/]
• 7. Randomization and placebo effects in clinical trials of major ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC11799522/]
• 8. The challenges of comparing results between placebo ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC4004366/]
• 9. Drug-placebo additivity in randomized clinical trials - PMC [https://pmc.ncbi.nlm.nih.gov/articles/PMC7168700/]
• 10. Placebo response and effect in randomized clinical trials [https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-021-05454-8]
• 11. Placebo effects in randomized trials of pharmacological ... [https://www.nature.com/articles/s41380-024-02638-x]
• 12. Digital Informed Consent/Assent in Clinical Trials Among ... [https://humanfactors.jmir.org/2025/1/e65569]
• 13. influencing Factors of comprehension for information ... informed [https://pubmed.ncbi.nlm.nih.gov/6569032/]
• 14. The reality of informed consent: empirical studies on patient ... [https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-020-04969-w]
• 15. Social Determinants of Health and Informed Consent ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC10714248/]
• 16. Factors Influencing Informed Consent Preferences in Digital ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC11803319/]
• 17. Journal of Medical Internet Research - Factors Influencing Informed ... [https://www.jmir.org/2025/1/e63349/]
• 18. Assessing Comprehension of Informed Consent in ... [https://www.sciencedirect.com/science/article/pii/S0010782425002422]
• 19. of Comprehension and voluntary participation in... informed consent [https://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-024-01033-z]
• 20. Effectiveness of Telehealth Versus In-Person Informed Consent [https://pubmed.ncbi.nlm.nih.gov/40053795/]
• 21. Informed consent in clinical research: Revisiting few ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC3601699/]
• 22. Guiding Principles for Ethical Research [https://www.nih.gov/health-information/nih-clinical-research-trials-you/guiding-principles-ethical-research]
• 23. Comprehension and Informed Consent: Assessing the ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC4819424/]
• 24. Designing the Consent Process - UW Research [https://www.washington.edu/research/hsd/guidance/consent/design/]
• 25. Research Ethics and Informed Consent [https://researchbasics.education.uconn.edu/ethics-and-informed-consent/]
• 26. Audio‐visual presentation of information for informed consent ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC6599866/]
• 27. Pictorial art for gaining informed consent in low-literacy ... [https://www.sciencedirect.com/science/article/pii/S0738399125001168]
• 28. Using provocative design to foster electronic informed consent ... [https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-02039-6]
• 29. Informed consent process in clinical trials: development of ... [https://www.sciencedirect.com/science/article/pii/S1130634323002003]
• 30. Improving understanding in the research informed consent ... [https://bmcmedethics.biomedcentral.com/articles/10.1186/1472-6939-14-28]
• 31. Comparative Effectiveness of eConsent: Systematic Review [https://pmc.ncbi.nlm.nih.gov/articles/PMC10504628/]
• 32. Assessing Comprehension During Reading with the ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC3725311/]
• 33. Assessing ChatGPT Ability to Answer Common Patient ... [https://journaloei.scholasticahq.com/article/137257]
• 34. Improving Comprehension of Consent Forms in Online ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12048739/]
• 35. Differences in rural and urban patient perceptions of ... - PMC [https://pmc.ncbi.nlm.nih.gov/articles/PMC12628826/]
• 36. The Performance of the Surrogate Informed Consent ... [https://www.sciencedirect.com/science/article/pii/S0012369225006890]
• 37. Co-designing and pilot-testing an infographic to support the ... [https://researchinvolvement.biomedcentral.com/articles/10.1186/s40900-025-00705-3]
• 38. The impact of text availability on task-demands ... [https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2025.1593197/full]
• 39. Questionnaire Use and Development in Health Research [https://www.mdpi.com/2673-8392/5/2/65]
• 40. Comparing Attitudes Toward Different Consent Mediums [https://humanfactors.jmir.org/2024/1/e53113/]
• 41. a mixed methods study within a trial (SWAT) [https://pmc.ncbi.nlm.nih.gov/articles/PMC12032667/]
• 42. An evaluation of the process of informed consent [https://pmc.ncbi.nlm.nih.gov/articles/PMC8371296/]
• 43. Current global practice and implications for future research ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12352677/]
• 44. Assessment of readability of informed consent forms ... [https://www.sciencedirect.com/science/article/pii/S2352578925000554]
• 45. Participants' Comprehension of the Informed Consent in an ... [https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.656822/full]
• 46. Clinical trials are becoming more complex: a machine ... [https://www.nature.com/articles/s41598-024-53211-z]
• 47. A Systematic Review of Digital Consent Tools to Enhance ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12596901/]
• 48. Effectiveness of an Interactive Digital Intervention Program on ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12444212/]
• 49. Clinical Research Technology: 10 Powerful Innovations in ... [https://lifebit.ai/blog/clinical-research-technology/]
• 50. Building a Digital Health Research Platform to Enable ... [https://www.jmir.org/2025/1/e60189/]
• 51. Decentralized Clinical Trial Platforms in 2025 - Castor EDC [https://www.castoredc.com/insight-briefs/decentralized-clinical-trial-platforms-in-2025-a-practical-guide-for-clinical-operations/]
• 52. Health Literacy in a Social Context: Review of Quantitative ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC6607851/]
• 53. Improving Health Literacy Through Medical Communications [https://pubrica.com/academy/patient-education/improve-health-literacy-medical-communications/]
• 54. Impact of low health literacy on patients' health outcomes [https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-022-08527-9]
• 55. The Effect of Age on Electronic Health Literacy: Mixed-Method ... [https://humanfactors.jmir.org/2019/2/e11480/]
• 56. Prescribing Information Resources [https://www.fda.gov/drugs/fdas-labeling-resources-human-prescription-drugs/prescribing-information-resources]
• 57. Patient-Focused Drug Development Guidance Series [https://www.fda.gov/drugs/development-approval-process-drugs/fda-patient-focused-drug-development-guidance-series-enhancing-incorporation-patients-voice-medical]
• 58. Beyond Translation: Promoting a New National Standard ... [https://nam.edu/perspectives/beyond-translation-promoting-a-new-national-standard-for-equity-in-health-materials-translated-from-english/]
• 59. Extended discussion of information for informed consent ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC6483689/]
• 60. The Effect of Discharge Training Based on Teach‐Back ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12285212/]
• 61. Teach-back: A systematic review of implementation and impacts [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231350]
• 62. Teach-back: A systematic review of implementation and impacts [https://pmc.ncbi.nlm.nih.gov/articles/PMC7156054/]
• 63. Use and Effectiveness of the Teach-Back Method in Patient ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC6590951/]
• 64. Development and evaluation of pharmacist-provided teach ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC10124684/]
• 65. Effectiveness and Implementation of Teach-Back as an ... [https://www.hsrd.research.va.gov/publications/management_briefs/default.cfm?ManagementBriefsMenu=eBrief-no236&eBriefTitle=Effectiveness+and+Implementation+of+Teach-Back+as+an+Approach+to+Patient+Education%3A+A+Systematic+Review]
• 66. Oncologists' knowledge, practices and ethical opinions ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC12247256/]
• 67. Therapeutic misconception and the appreciation of risks in ... [https://www.sciencedirect.com/science/article/abs/pii/S0277953603003381]
• 68. New Informed Consent Expectations Should Aid ... [https://acrpnet.org/2024/11/21/new-informed-consent-expectations-should-aid-participants-understanding-may-catch-professionals-off-guard]
• 69. Informed Consent Forms: A Guide to Ethics & Regulation [https://intuitionlabs.ai/articles/informed-consent-clinical-trial-ethics]
• 70. Comparing a Multimedia Digital Informed Consent Tool With ... [https://pmc.ncbi.nlm.nih.gov/articles/PMC8564662/]
• 71. Making clinical trials more patient-centered using digital ... [https://www.rti.org/rti-press-publication/making-clinical-trials-patient-centered-using-digital-interactive-e-consent-tools]
• 72. Comparative Effectiveness of eConsent: Systematic Review [https://www.jmir.org/2023/1/e43883/]
• 73. Comparing shared decision making using a paper and ... [https://www.sciencedirect.com/science/article/pii/S1479666X22000877]
• 74. eConsent as the digital foundation for modern clinical trials [https://www.drugdiscoverytrends.com/econsent-as-the-digital-foundation-for-modern-clinical-trials/]
• 75. Top 10 eConsent Platforms for clinical trials [https://www.eclevarmedtech.com/en/top-10-econsent-platforms-for-clinical-trials/]
• 76. The USA's Food and Drug Administration and informed ... [https://blogs.bmj.com/medical-ethics/2025/03/19/the-usas-food-and-drug-administration-and-informed-consent/]
• 77. 臨床試驗流程介紹 [https://novotech-cro.com/ct/blog/understanding-clinical-trial-process]
• 78. Artificial Intelligence and the future of clinical trials - PMC [https://pmc.ncbi.nlm.nih.gov/articles/PMC12490578/]
• 79. AI could personalise clinical trial consent, but privacy ... [https://www.clinicaltrialsarena.com/news/ai-could-personalise-clinical-trial-consent-but-privacy-concerns-remain/]
• 80. 生成式人工智能研究进展：机遇、挑战与未来展望 - MXDIA -MXDIA乂媒体 [https://www.mxdia.com/posts/9bzZk4eb39A3]
• 81. Five key trends in China's generative AI market in 2025 | Roland Berger [https://www.rolandberger.com/en/Insights/Publications/Five-key-trends-in-China-s-generative-AI-market-in-2025.html]
• 82. How AI Is Transforming Clinical Trials | AHA [https://www.aha.org/aha-center-health-innovation-market-scan/2025-10-21-how-ai-transforming-clinical-trials]
• 83. U.S. FDA's Updated Informed Consent Guidelines [https://about.citiprogram.org/blog/navigating-fdas-updated-informed-consent-guidelines/]
• 84. FCC One-to-One Consent Changes for 2025: What You Need ... [https://trestleiq.com/fcc-one-to-one-consent-changes-for-2025-what-you-need-to-know/]
• 85. User Data Consent: Regional Trends in 2025 [https://peerstorage.co/user-data-consent-regional-trends-in-2025/?srsltid=AfmBOoounpZPAFF7yRFJHMKDztd-XlfEUaziwTgc3IUqb8xV2Zlbj1DS]
• 86. Is Your Cookie Consent Still Valid in 2025? [https://cookie-script.com/guides/is-your-cookie-consent-still-valid-in-2025]
• 87. New Regulatory Guidance Referencing Consent [https://ge2p2global-centerforinformedconsentintegrity.org/category/new-regulatory-guidance-referencing-consent/]
• 88. A user-driven consent platform for health data sharing in ... [https://www.nature.com/articles/s41746-025-02147-3]