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Leveraging crowdsourcing methods to collect qualitative data in addiction science: Narratives of non-medical prescription opioid, heroin, and fentanyl use
استفاده بی نظیر از روش های تأمین منابع انبوه برای جمع آوری داده های کیفی در علوم اعتیاد: روایات استفاده از داروهای افیونی ، هروئین و فنتانیل با تجویز غیر پزشکی-2020 Background: Online crowdsourcing methods have proved useful for studies of diverse designs in the behavioral
and addiction sciences. The remote and online setting of crowdsourcing research may provide easier access to
unique participant populations and improved comfort for these participants in sharing sensitive health or behavioral
information. To date, few studies have evaluated the use of qualitative research methods on crowdsourcing
platforms and even fewer have evaluated the quality of data gathered. The purpose of the present
analysis was to document the feasibility and validity of using crowdsourcing techniques for collecting qualitative
data among people who use drugs.
Methods: Participants (N=60) with a history of non-medical prescription opioid use with transition to heroin or
fentanyl use were recruited using Amazon Mechanical Turk (mTurk). A battery of qualitative questions was
included indexing beliefs and behaviors surrounding opioid use, transition pathways to heroin and/or fentanyl
use, and drug-related contacts with structural institutions (e.g., health care, criminal justice).
Results: Qualitative data recruitment was feasible as evidenced by the rapid sampling of a relatively large
number of participants from diverse geographic regions. Computerized text analysis indicated high ratings of
authenticity for the provided narratives. These authenticity percentiles were higher than the average of general
normative writing samples as well as than those collected in experimental settings.
Conclusions: These findings support the feasibility and quality of qualitative data collected in online settings,
broadly, and crowdsourced settings, specifically. Future work among people who use drugs may leverage
crowdsourcing methods and the access to hard-to-sample populations to complement existing studies in the
human laboratory and clinic as well as those using other digital technology methods. Keywords: Crowdsourcing | Heroin | Mechanical Turk | Opioid | Qualitative | Mixed method |
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