Recruiting Nurses via Social Media for Survey Studies.

2020 
BACKGROUND Nurses are a difficult population to recruit for research. Barriers to recruitment of nurses include survey fatigue, hospital structures and institutional review boards as gatekeepers to accessing participants, and limited generalizability of findings. Social media present innovative opportunities to recruit participants for survey research. However, there is limited information about best practices for recruiting nurses through social media. OBJECTIVES The aim of this report was to examine the advantages and disadvantages of and determine the best practices for recruiting nurses for survey studies via social media. METHODS We examined recruitment strategies of three survey studies involving nurse participants. Each study used social exchange theory and leverage saliency theory to guide recruitment. The studies included were: (a) Travel Nurse Onboarding study which recruited participants from a single closed group on Facebook; (b) Presenteeism and Nursing study where participants were recruited using association listservs, health care organizations, and paid ads and postings on social media; and (c) the Pain and Nursing study in which participants were recruited through social media, association listservs, and in person at conferences. RESULTS Social media offer accessible, low-cost, high-yield approaches to recruitment of nurses for survey studies. DISCUSSION Useful strategies for crafting effective recruitment via social media are presented, including how, where, when, and how often to post. The generalizability of social media research is also discussed. Suggestions are provided for researchers using social media as well as guidelines for institutional review boards to address grey areas of social media research. Data integrity protection techniques are proposed to ensure social media survey data are not corrupted by malicious bots. This report outlines best practices for the recruitment of nurses for survey studies using social media.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    16
    References
    2
    Citations
    NaN
    KQI
    []