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Measuring online endorsement of prescription opioids abuse: an integrative methodology.

机译:测量处方阿片类药物滥用的在线认可:一种综合方法。

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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.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.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.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.
机译:跟踪处方阿片类药物滥用者对化合物的认可的能力可能对预测滥用者的偏好很有价值。我们制定了一项指标,即认可率(ERo),以探讨量化在网上发布有关处方阿片类药物产品的阿片类药物滥用者表达的情感的可行性.2010年4月1日至2011年3月31日之间撰写的互联网帖子以及相关文章鉴定了六个处方类阿片化合物(羟考酮ER,氢可酮,氢吗啡酮,羟吗啡酮,吗啡ER和曲马多),并进行了质量编码。混合效果多项式逻辑回归用于对每种化合物观察到认可,劝阻,混合或不清楚信息的可能性进行建模。估算了每种化合物的背书/劝退比(ERo)和背书/劝阻比(RERo)。在12到838个互联网帖子的研究样本中,可以建立背书等级,其中羟吗啡酮为最高批准(ERoα=?7.39),然后是氢吗啡酮(ERo?=?5.02),氢可酮(ERo?=?3.53),羟考酮ER(ERo?=?3.23),吗啡ER(ERo?== 2.71)和曲马多(ERo≥1.76)。产品的相对排名要求考虑到管理途径。本研究通过制定一种度量标准来评估现有处方药监测方法,以评估特定处方阿片类药物的认可程度,这一观点是从互联网社区的角度来看的。在检查吸毒者对各种产品的偏好时,必须考虑给药途径。这项研究没有评估新指标在不同药物滥用率分类方面是否有效。有必要对外部验证研究进行进一步的研究。

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