Computational protocol: Linguistic Strategies for Improving Informed Consent in Clinical Trials Among Low Health Literacy Patients

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Protocol publication

[…] Preliminary analyses were conducted to determine if randomization procedures were effective. Chi-square tests and analysis of variance (ANOVA) were used to verify there were no statistically significant differences among the treatment groups with regard to study covariates. A series of analyses were conducted to determine the effects of message condition on comprehension of randomization, as well as model how cognitive and affective variables influence behavioral intention to participate in RCTs. Analysis of covariance (ANCOVA) was used to determine the effect of the four message conditions (control, plain language, gambling metaphor, and benign metaphor) on comprehension of randomization in a RCT, using age, sex, education, race/ethnicity, and perceived severity of cancer as covariates. Pairwise comparisons were performed using a Sidak correction. Linear regression was used to examine the relationship between comprehension and behavioral intention, using age, sex, education, race/ethnicity, perceived severity of cancer, health literacy, and dummy codes for message conditions as covariates. Message conditions were included as covariates via comparison coding in the linear regression to account for their statistically significant influence on comprehension, as indicated in the ANCOVA results.Version 2.15 of the SPSS PROCESS macro was used to test for simple moderation (ie, Model 1) with a multicategorical focal predictor and serial mediation (ie, Model 6) (,). In the simple moderation model, two analyses were run with message condition set as the focal predictor, health literacy as the moderator, and comprehension as the dependent variable. Age, sex, education, race/ethnicity, and perceived severity of cancer were included as covariates in both analyses. The first analysis implemented indicator coding to determine differences in comprehension between the control condition and each of the other conditions for varying levels of health literacy. The second analysis applied Helmert coding to identify differences in comprehension between the metaphorical conditions and the plain language condition for varying levels of health literacy. Helmert coding allows comparisons between levels of a nominal multicategorical variable ().In the serial mediation model, personal relevance and anxiety were tested as mediators operating in sequence to explain the indirect effect of comprehension on behavioral intention. Age, sex, education, race/ethnicity, perceived severity of cancer, health literacy, and message conditions were included as covariates. The message conditions were not included as focal predictors in the serial mediation analysis because of limitations of the software. Statistical mediation analysis with a multicategorical independent variable cannot be conducted with mediators in sequence (Model 6) (). Given the documented influence of the message conditions and health literacy on comprehension, it is important to control for these effects when testing the proposed theoretical model. Bootstrapping was used to construct percentile-based, bias-corrected 95% confidence intervals (CIs) for specific and total indirect effects (). All statistical tests were two-sided, and a P value of less than .05 was considered statistically significant. […]

Pipeline specifications

Software tools metaphor, SPSS
Applications Miscellaneous, GWAS
Organisms Homo sapiens
Diseases Neoplasms