Measuring online endorsement of prescription opioids abuse: an integrative methodology.
OBJECTIVE
The ability to track prescription opioid abusers' endorsement of compounds may be valuable in forecasting abuser's preferences. We developed a metric, referred to as the Endorsement Ratio (ERo), to explore the feasibility of quantifying the sentiment expressed by opioid abusers who post online about prescription opioid products.


METHODS
Internet posts written between April 1, 2010 and March 31, 2011 and related to six prescription opioid compounds (oxycodone ER, hydrocodone, hydromorphone, oxymorphone, morphine ER, and tramadol) were identified and qualitatively coded. A mixed effects multinomial logistic regression was employed to model the probability of observing endorsing, discouraging, mixed, or unclear messages per compound. Endorsement-to-discouragement ratio (ERo) and ratio of endorsement-to-discouragement ratios (RERo) were estimated for each compound.


RESULTS
In the study sample of 12 838 Internet posts, a ranking of endorsement could be established, with oxymorphone as most endorsed (ERo = 7.39), followed by hydromorphone (ERo = 5.02), hydrocodone (ERo = 3.53), oxycodone ER (ERo = 3.23), morphine ER (ERo = 2.71), and tramadol (ERo = 1.76). Relative rankings of products required that route of administration be considered.


CONCLUSIONS
This study expands existing Internet monitoring approaches by developing a metric to estimate the endorsement of specific prescription opioid compounds as viewed through the lens of Internet communities. Route of administration must be taken into account when examining preferences of drug abusers for various products. This study did not assess whether the novel metric is valid with respect to classification of abuse rates of different drugs. Further studies examining external validation studies are warranted.
Inflexxion, Inc., 320 Needham Street, Suite 100, Newton, MA 02464, USA. emcnaughton@inflexxion.com
Emily C
EC
McNaughton
Ryan A
RA
Black
Mirella G
MG
Zulueta
Simon H
SH
Budman
Stephen F
SF
Butler
D000701:Analgesics, Opioid; D016903:Drug Monitoring / Q000379:methods* / Q000639:trends; D055030:Drug Users / Q000706:statistics & numerical data*; D006801:Humans; D009862:Online Systems / Q000592:standards* / Q000639:trends; D055553:Prescription Drugs
D000701:Analgesics, Opioid; D055553:Prescription Drugs