Objective: To establish whether age, gender or years in education influence individual likelihood to consent to Parkinson’s (PD) research.

Background: Multiple factors may act as barriers to consent and engagement in research. These include health literacy level, study understanding, concerns about sample donation, and trust in research. Previous findings highlight how demographic characteristics and education level may influence the impact of these barriers. Understanding factors affecting consent, in our cohort, will lead to targeted recruitment and resource provision in these areas.

Method: PREDICT-PD is a longitudinal, UK-based cohort study. The present study is cross-sectional and observational. Inclusion criteria were that participants were 50-80 years old, without a diagnosis of PD and a UK resident at the time of enrolment (baseline). Consent statements, age, ethnicity, gender and years in education were extracted from PREDICT-PD survey data. The outcome variable was consent, grouped by whether participants had consented yes to all six mandatory statements, or not. Participants who refused one or more of these statements were defined as ‘not consented to all’. Descriptive analyses are presented with means, standard deviations, frequencies and percentages. A multivariate binary logistic regression assessed relationships between the independent variables (age, gender, years in education) and consent as the binary dependent variable. Ethnicity was removed as an independent variable due to insufficient numbers across groups.

Results: The sample included 3144 participants (58.5% Female, 97.4% White ethnic background, mean age in years: 70.06, SD 5.99, mean years in education: 17.57, SD 4.39). A multivariate binary logistic regression revealed that, in this sample, being male (OR: 1.923, p=0.005) and having an increased number of years in education (OR:1.053, p=0.041) were both associated with increased likelihood of consent. Age was not associated with likelihood of consent here.

Conclusion: Initial associations between gender, years in education, and likelihood to consent were revealed. Future work should increase ethnicity data, examine likelihood to consent to individual statements (e.g. biosample collection) and capture qualitative data to further explore barriers and promoters of engagement.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/likelihood-to-consent-within-the-predict-pd-cohort-identifying-potential-barriers-or-promoters-of-involvement-in-longitudinal-parkinsons-research/