Measuring attractiveness for abuse of prescription opioids.
OBJECTIVE
Prescription opioids are the second most misused/abused drug in the United States behind only marijuana. Recreational prescription opioid users appear to prefer some products over others; however, the extent to which attributes of any particular formulation account for such preferences has yet to be determined. The Opioid Attractiveness Technology Scaling was developed to identify the particular features of a prescription opioid that are relevant to its attractiveness for recreational use, and to use these features to model attractiveness for recreational use of particular prescription opioid formulations.


METHODS
Four hundred and ninety-one self-reported recreational prescription opioid users identified 43 product features as being relevant to determining whether a product is "attractive" or "unattractive" for recreational use. Average ratings were used to determine appropriate weights to be applied to the features. A factor analysis yielded 10, highly differentiated factors. Five hundred and sixty-four prescription opioid abusers were then asked to rate the extent to which the 43 features identified in Study 1 were relevant to specific prescription opioid products they had used.


RESULTS
Respondents provided an overall preference rating of these products and a model was created. A random intercept model yielded a significant pseudo R(2) of 0.14 (chi-square = 310.02, degrees of freedom [df] = 10, P < 0.001). The model fit least well, albeit significantly, for abusers who preferred to swallow the drug (pseudo R(2) = 0.06; chi-square = 55.52, df = 10, P < 0.001) and best for those who preferred to inject (pseudo R(2) = 0.37; chi-square = 199.34, df = 10, P < 0.001).


CONCLUSIONS
The relevance of the model is discussed along with possible modifications that might allow prediction of "attractiveness" of "abuse deterrent" formulations that have not yet been marketed.
Butler
Stephen F
SF
Inflexxion, Inc., Newton, Massachusetts, USA. sfbutler@inflexxion.com
Fernandez
Kathrine C
KC
Chang
Alan
A
Benoit
Christine
C
Morey
Leslie C
LC
Black
Ryan
R
Katz
Nathaniel
N
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000701:Analgesics, Opioid; D002626:Chemistry, Pharmaceutical; D002648:Child; D003627:Data Interpretation, Statistical; D003710:Demography; D016527:Drug Costs; D005260:Female; D006306:Health Surveys; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D009293:Opioid-Related Disorders / Q000191:economics / Q000523:psychology*; D010146:Pain / Q000150:complications; D055553:Prescription Drugs; D055815:Young Adult
D000701:Analgesics, Opioid; D055553:Prescription Drugs