Factors affecting enrollment in literacy studies for English- and Spanish-speaking cancer patients

Stat Med. 2008 Sep 10;27(20):4119-31. doi: 10.1002/sim.3259.


Background: Study participation bias can affect inferences regarding outcomes.

Objective: The objective is to compare characteristics of participants and non-participants of two literacy studies.

Methods: Two studies of literacy and health-related quality of life were conducted in English- and Spanish-speaking cancer patients. Patients had a range of literacy skills, and each enrolled patient received $20.

Results: Nine hundred and twenty-two English-speaking patients were approached. Among the 651 who met eligibility criteria, 420 were enrolled (64.5 per cent). Four hundred and eighty-seven Spanish-speaking patients were approached. Among the 455 who met eligibility criteria, 414 were enrolled (91.0 per cent) (p<0.001). Multiple imputations were performed to impute missing data. Multivariable logistic regression revealed that recruiting site was the only factor predictive of enrollment in Spanish-speaking patients. Age, education, and recruiting site were important predictors in English-speaking patients. Sensitivity analysis using patients with complete data generated similar results.

Conclusions: Spanish-speaking patients enrolled at a much higher rate than English-speaking patients, which is encouraging for future research in this underserved population. One important literacy-related factor (education) did not affect enrollment in Spanish-speaking patients, suggesting that there was no selection bias in this study. Recruiting sites with more indigent patients and long clinic waiting times had higher enrollment, suggesting that monetary compensation and time availability may be important considerations in study participation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Analysis of Variance
  • Attitude to Health / ethnology*
  • Computer Literacy
  • Educational Status
  • Female
  • Hispanic or Latino
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Neoplasms / ethnology*
  • Neoplasms / psychology*
  • Patient Education as Topic*
  • Patient Selection*
  • Reproducibility of Results
  • Selection Bias
  • User-Computer Interface
  • White People