A randomized trial to determine the impact on compliance of a psychophysical peripheral cue based on the Elaboration Likelihood Model

Objective: Non-compliance in clinical studies is a significant issue, but causes remain unclear. Utilizing the Elaboration Likelihood Model of persuasion, this study assessed the psychophysical peripheral cue ‘Interactive Voice Response System (IVRS) call frequency’ on compliance. Methods: 71 participants were randomized to once daily (OD), twice daily (BID) or three times daily (TID) call schedules over two weeks. Participants completed 30-item cognitive function tests at each call. Compliance was defined as proportion of expected calls within a narrow window (± 30 min around scheduled time), and within a relaxed window (− 30 min to + 4 h). Data were analyzed by ANOVA and pairwise comparisons adjusted by the Bonferroni correction. Results: There was a relationship between call frequency and compliance. Bonferroni adjusted pairwise comparisons showed significantly higher compliance (p = 0.03) for the BID (51.0%) than TID (30.3%) for the narrow window; for the extended window, compliance was higher (p = 0.04) with OD (59.5%), than TID (38.4%). Conclusion: The IVRS psychophysical peripheral cue call frequency supported the ELM as a route to persuasion. The results also support OD strategy for optimal compliance. Models suggest specific indicators to enhance compliance with medication dosing and electronic patient diaries to improve health outcomes and data integrity respectively

PRO Data Collection in Clinical Trials Using Mixed Modes: Report of the ISPOR PRO Mixed Modes Good Research Practices Task Force

AbstractThe objective of this report was to address the use and mixing of data collection modes within and between trials in which patient-reported outcome (PRO) end points are intended to be used to support medical product labeling. The report first addresses the factors that should be considered when selecting a mode or modes of PRO data collection in a clinical trial, which is often when mixing is first considered. Next, a summary of how to "faithfully" migrate instruments is presented followed by a section on qualitative and quantitative study designs used to evaluate measurement equivalence of the new and original modes of data collection. Finally, the report discusses a number of issues that must be taken into account when mixing modes is deemed necessary or unavoidable within or between trials, including considerations of the risk of mixing at different levels within a clinical trial program and mixing between different types of platforms. In the absence of documented evidence of measurement equivalence, it is strongly recommended that a quantitative equivalence study be conducted before mixing modes in a trial to ensure that sufficient equivalence can be demonstrated to have confidence in pooling PRO data collected by the different modes. However, we also strongly discourage the mixing of paper and electronic field-based instruments and suggest that mixing of electronic modes be considered for clinical trials and only after equivalence has been established. If proceeding with mixing modes, it is important to implement data collection carefully in the trial itself in a planned manner at the country level or higher and minimize ad hoc mixing by sites or individual subjects. Finally, when mixing occurs, it must be addressed in the statistical analysis plan for the trial and the ability to pool the data must be evaluated to then evaluate treatment effects with mixed modes data. A successful mixed modes trial requires a "faithful migration," measurement equivalence established between modes, and carefully planned implementation to minimize the risk of increased measurement error impacting the power of the trial to detect a treatment effect