Recruitment via social media: advantages and potential biases.
Digit Health
; 5: 2055207619867223, 2019.
Article
en En
| MEDLINE
| ID: mdl-31431827
ABSTRACT
BACKGROUND:
Adolescent and young adult (AYA) cancer survivors are under-represented in research. Social media is increasingly used for recruitment given its ability to reach large audiences. Differences in participant characteristics and potential biases due to recruitment source are not well understood.PURPOSE:
This study aimed to (a) compare recruitment strategies (hospital-based v. social media) in enrollment metrics, and (b) among enrolled participants, evaluate group differences in patient characteristics and patient reported outcomes (PROs).METHODS:
Preliminary data from a cancer and fertility study with female AYAs were evaluated. Hospital-based recruitment used electronic medical records (EMR) to identify eligible patients. Social media recruitment involved posting on partner organizations' social media outlets. PROs included validated measures related to the parent study. Descriptive statistics evaluated recruitment metrics. Independent samples t-tests and chi-square identified differences in participant characteristics and PROs based on recruitment.RESULTS:
Social media yielded a higher enrollment rate (37%; n = 54/146) compared with hospital-based recruitment (7%; n = 21/289) and required fewer study resources. Compared with hospital-based recruitment, participants from social media were more likely to be White (p = 0.01), with a longer time since treatment (p = 0.03); and reported higher levels of reproductive concern (p = 0.004) and negative mood (p = 0.02), and more negative illness perceptions (ps < 0.05).CONCLUSION:
Recruitment via social media may be a more effective and efficient strategy compared with hospital-based methods. However, group differences were identified that could bias findings and limit generalizability. Advantages of social media should be considered with an understanding of how methodology may impact enrollment and results.
Texto completo:
1
Base de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Digit Health
Año:
2019
Tipo del documento:
Article