Historique
Article de Périodique
Innovative recruitment using online networks: lessons learned from an online study of alcohol and other drug use utilizing a web-based, Respondent-Driven Sampling (webRDS) strategy (2012)
Auteur(s) :
BAUERMEISTER, J. A. ;
ZIMMERMAN, M. A. ;
JOHNS, M. M. ;
GLOWACKI, P. ;
STODDARD, S. ;
VOLZ, E.
Année
2012
Page(s) :
834-838
Langue(s) :
Anglais
Domaine :
Alcool / Alcohol ; Drogues illicites / Illicit drugs
Discipline :
EPI (Epidémiologie / Epidemiology)
Thésaurus géographique
ETATS-UNIS
Thésaurus mots-clés
ENQUETE
;
METHODE
;
INTERNET
;
PREVALENCE
;
COMPARAISON
;
JEUNE ADULTE
;
RESEAUX SOCIAUX
Autres mots-clés
Résumé :
OBJECTIVE: We used a web version of Respondent-Driven Sampling (webRDS) to recruit a sample of young adults (ages 18-24) and examined whether this strategy would result in alcohol and other drug (AOD) prevalence estimates comparable to national estimates (National Survey on Drug Use and Health [NSDUH]).
METHOD: We recruited 22 initial participants (seeds) via Facebook to complete a web survey examining AOD risk correlates. Sequential, incentivized recruitment continued until our desired sample size was achieved. After correcting for webRDS clustering effects, we contrasted our AOD prevalence estimates (past 30 days) to NSDUH estimates by comparing the 95% confidence intervals of prevalence estimates.
RESULTS: We found comparable AOD prevalence estimates between our sample and NSDUH for the past 30 days for alcohol, marijuana, cocaine, Ecstasy (3,4-methylenedioxymethamphetamine, or MDMA), and hallucinogens. Cigarette use was lower than NSDUH estimates.
CONCLUSIONS: WebRDS may be a suitable strategy to recruit young adults online. We discuss the unique strengths and challenges that may be encountered by public health researchers using webRDS methods.
METHOD: We recruited 22 initial participants (seeds) via Facebook to complete a web survey examining AOD risk correlates. Sequential, incentivized recruitment continued until our desired sample size was achieved. After correcting for webRDS clustering effects, we contrasted our AOD prevalence estimates (past 30 days) to NSDUH estimates by comparing the 95% confidence intervals of prevalence estimates.
RESULTS: We found comparable AOD prevalence estimates between our sample and NSDUH for the past 30 days for alcohol, marijuana, cocaine, Ecstasy (3,4-methylenedioxymethamphetamine, or MDMA), and hallucinogens. Cigarette use was lower than NSDUH estimates.
CONCLUSIONS: WebRDS may be a suitable strategy to recruit young adults online. We discuss the unique strengths and challenges that may be encountered by public health researchers using webRDS methods.
Affiliation :
Department of Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
Cote :
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