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Background: Substance use is a global issue, with around 30 to 35 million individuals estimated to have a substance-use disorder. Motivational interviewing (MI) is a client-centred method that aims to strengthen a person's motivation and commitment to a specific goal by exploring their reasons for change and resolving ambivalence, in an atmosphere of acceptance and compassion. This review updates the 2011 version by Smedslund and colleagues., Objectives: To assess the effectiveness of motivational interviewing for substance use on the extent of substance use, readiness to change, and retention in treatment., Search Methods: We searched 18 electronic databases, six websites, four mailing lists, and the reference lists of included studies and reviews. The last search dates were in February 2021 and November 2022., Selection Criteria: We included randomised controlled trials with individuals using drugs, alcohol, or both. Interventions were MI or motivational enhancement therapy (MET), delivered individually and face to face. Eligible control interventions were no intervention, treatment as usual, assessment and feedback, or other active intervention., Data Collection and Analysis: We used standard methodological procedures expected by Cochrane, and assessed the certainty of evidence with GRADE. We conducted meta-analyses for the three outcomes (extent of substance use, readiness to change, retention in treatment) at four time points (post-intervention, short-, medium-, and long-term follow-up)., Main Results: We included 93 studies with 22,776 participants. MI was delivered in one to nine sessions. Session durations varied, from as little as 10 minutes to as long as 148 minutes per session, across included studies. Study settings included inpatient and outpatient clinics, universities, army recruitment centres, veterans' health centres, and prisons. We judged 69 studies to be at high risk of bias in at least one domain and 24 studies to be at low or unclear risk. Comparing MI to no intervention revealed a small to moderate effect of MI in substance use post-intervention (standardised mean difference (SMD) 0.48, 95% confidence interval (CI) 0.07 to 0.89; I 2 = 75%; 6 studies, 471 participants; low-certainty evidence). The effect was weaker at short-term follow-up (SMD 0.20, 95% CI 0.12 to 0.28; 19 studies, 3351 participants; very low-certainty evidence). This comparison revealed a difference in favour of MI at medium-term follow-up (SMD 0.12, 95% CI 0.05 to 0.20; 16 studies, 3137 participants; low-certainty evidence) and no difference at long-term follow-up (SMD 0.12, 95% CI -0.00 to 0.25; 9 studies, 1525 participants; very low-certainty evidence). There was no difference in readiness to change (SMD 0.05, 95% CI -0.11 to 0.22; 5 studies, 1495 participants; very low-certainty evidence). Retention in treatment was slightly higher with MI (SMD 0.26, 95% CI -0.00 to 0.52; 2 studies, 427 participants; very low-certainty evidence). Comparing MI to treatment as usual revealed a very small negative effect in substance use post-intervention (SMD -0.14, 95% CI -0.27 to -0.02; 5 studies, 976 participants; very low-certainty evidence). There was no difference at short-term follow-up (SMD 0.07, 95% CI -0.03 to 0.17; 14 studies, 3066 participants), a very small benefit of MI at medium-term follow-up (SMD 0.12, 95% CI 0.02 to 0.22; 9 studies, 1624 participants), and no difference at long-term follow-up (SMD 0.06, 95% CI -0.05 to 0.17; 8 studies, 1449 participants), all with low-certainty evidence. There was no difference in readiness to change (SMD 0.06, 95% CI -0.27 to 0.39; 2 studies, 150 participants) and retention in treatment (SMD -0.09, 95% CI -0.34 to 0.16; 5 studies, 1295 participants), both with very low-certainty evidence. Comparing MI to assessment and feedback revealed no difference in substance use at short-term follow-up (SMD 0.09, 95% CI -0.05 to 0.23; 7 studies, 854 participants; low-certainty evidence). A small benefit for MI was shown at medium-term (SMD 0.24, 95% CI 0.08 to 0.40; 6 studies, 688 participants) and long-term follow-up (SMD 0.24, 95% CI 0.07 to 0.41; 3 studies, 448 participants), both with moderate-certainty evidence. None of the studies in this comparison measured substance use at the post-intervention time point, readiness to change, and retention in treatment. Comparing MI to another active intervention revealed no difference in substance use at any follow-up time point, all with low-certainty evidence: post-intervention (SMD 0.07, 95% CI -0.15 to 0.29; 3 studies, 338 participants); short-term (SMD 0.05, 95% CI -0.03 to 0.13; 18 studies, 2795 participants); medium-term (SMD 0.08, 95% CI -0.01 to 0.17; 15 studies, 2352 participants); and long-term follow-up (SMD 0.03, 95% CI -0.07 to 0.13; 10 studies, 1908 participants). There was no difference in readiness to change (SMD 0.15, 95% CI -0.00 to 0.30; 5 studies, 988 participants; low-certainty evidence) and retention in treatment (SMD -0.04, 95% CI -0.23 to 0.14; 12 studies, 1945 participants; moderate-certainty evidence). We downgraded the certainty of evidence due to inconsistency, study limitations, publication bias, and imprecision., Authors' Conclusions: Motivational interviewing may reduce substance use compared with no intervention up to a short follow-up period. MI probably reduces substance use slightly compared with assessment and feedback over medium- and long-term periods. MI may make little to no difference to substance use compared to treatment as usual and another active intervention. It is unclear if MI has an effect on readiness to change and retention in treatment. The studies included in this review were heterogeneous in many respects, including the characteristics of participants, substance(s) used, and interventions. Given the widespread use of MI and the many studies examining MI, it is very important that counsellors adhere to and report quality conditions so that only studies in which the intervention implemented was actually MI are included in evidence syntheses and systematic reviews. Overall, we have moderate to no confidence in the evidence, which forces us to be careful about our conclusions. Consequently, future studies are likely to change the findings and conclusions of this review., (Copyright © 2023 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Signal detection is routinely applied to spontaneous report safety databases in the pharmaceutical industry and by regulators. As an example, methods that search for increases in the frequencies of known adverse drug reactions for a given drug are routinely applied, and the results are reported to the health authorities on a regular basis. Such methods need to be sensitive to detect true signals even when some of the adverse drug reactions are rare. The methods need to be specific and account for multiplicity to avoid false positive signals when the list of known adverse drug reactions is long. To apply them as part of a routine process, the methods also have to cope with very diverse drugs (increasing or decreasing number of cases over time, seasonal patterns, very safe drugs versus drugs for life-threatening diseases). In this paper, we develop new nonparametric signal detection methods, directed at detecting differences between a reporting and a reference period, or trends within a reporting period. These methods are based on bootstrap and permutation distributions, and they combine statistical significance with clinical relevance. We conducted a large simulation study to understand the operating characteristics of the methods. Our simulations show that the new methods have good power and control the family-wise error rate at the specified level. Overall, in all scenarios that we explored, the method performs much better than our current standard in terms of power, and it generates considerably less false positive signals as compared to the current standard., (Copyright © 2018 John Wiley & Sons, Ltd.)

Purpose: The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR)., Methods: A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied., Results: There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity., Conclusions: Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis., (Copyright © 2011 John Wiley & Sons, Ltd.)

Two goals when counseling breastfeeding mothers taking medication are protecting the infant from adverse events and permitting necessary maternal therapy. Madadi et al. report a case-control study of neonatal and maternal opioid toxicity after codeine administration. Therapeutic considerations in counseling breastfeeding mothers include susceptibility to drug toxicity of the very young and/or premature infant, significant interindividual variations in drug response, the dose-response relationship with respect to drug toxicity, and the role of pharmacogenetics in both the mother and the infant. These host factors may combine in a particular patient to act synergistically to produce an adverse reaction.

We can now distinguish, in part, between nerve deafness and hair cell deafness through the use of otoacoustic emissions. We can also assess the efferent system by carefully quantifying the effects of contralateral stimulation on these same otoacoustic emissions. The suppression of transient evoked emissions by continuous contralateral white noise is an ostensibly small effect of 2 or 3 dB when studied over a 20-msec window. However, when subjected to microstructural analysis, the effect can exceed 6 to 8 dB in the zones from 10 to 20 msec after the stimulus has subsided. Temporal and spectral analyses reveal robust effects of contralateral lateral stimulation, although in any given normal subject it may be difficult to separate middle ear effects from efferent effects. Evidence is strong that the efferent effect is mediated in part by cholinergic-primarily nicotinic-receptors in the outer hair cell. However, a unique type of patient, who shows nearly normal pure-tone audiograms and absent ABRs, shows virtually no contralateral suppression of transient evoked emissions. Some other patients, with symptoms of Charcot-Marie-Tooth disease, may paradoxically show extremely poor audiograms, but perfectly normal evoked emissions along with absent contralateral suppression. The ABR, along with middle ear muscle reflexes and masking level differences, are all absent in these patients; we therefore think they have a disorder that desynchronizes most of their primary auditory nerve fibers and thereby disconnects them from any efferent activity or masking cancellation. The existence of such an auditory disorder, characterized by severe dysfunction in speech comprehension-especially when listening in noise-suggests that what appears to be a "central auditory imperception" might stem instead from a systemic peripheral primary neuropathy.

The auditory brainstem response to clicks of 60 dB sensation level was recorded with superimposed pure tones at six frequencies and four sensation levels in an attempt to simulate the effects of tinnitus on the auditory brainstem response. Changes in responses were assessed by subtracting the auditory brainstem response obtained to the click-plus-tone from the auditory brainstem response obtained to the immediately preceding click alone. The dyssynchrony created by exogenously produced pure tones was considerable and probably reflected adaptation of individual single units; however, the auditory brainstem response to clicks alone changed markedly from the beginning to the end of the experiment and confounded a simple interpretation of the results.

Widely used to study hepatic drug metabolism, antipyrine rapidly distributes in total body water. Antipyrine distribution was studied in seven lactating women. Duration of lactation ranged from 2 to 19 mo. In all subjects the drug was rapidly absorbed; in five women peak concentrations were attained in milk and saliva by 1 hr and in the other two women by 3 hr (first point at which collections were made). In two women in whom antipyrine was measured at 10-min intervals during the first hour, peak concentrations in both milk and saliva were attained by 10 min after antipyrine. The time course for antipyrine disappearance from milk paralleled that from saliva for each subject. Antipyrine half-life (t1/2) varied from 5.6 to 20.3 hr for saliva (mean +/- SD = 11.5 +/- 4.8) and from 5.7 to 21.7 hr for milk (mean +/- SD = 11.6 +/- 5.4). In the two women with the shortest salivary antipyrine t1/2 (5.6 and 7.5 hr), antipyrine was readministered many months later, after they had stopped lactating. The salivary antipyrine t1/2 rose from 5.6 to 13.3 hr in one subject and from 7.5 to 14.6 hr in the other. The corresponding decrease in antipyrine clearance was 0.93 to 0.55 and 1.41 to 0.60 ml/min/kg. This observation suggests that in some subjects lactation may influence drug metabolism. The amount of antipyrine available to each nursing infant was estimated by assuming the the infant nursed 3 ounces every 4 hr for 24 hr after maternal antipyrine administration. The amount of antipyrine available to the nursing infant was calculated to range from 3.0 to 11.1 mg (mean +/- SD = 6.4 +/- 2.9 mg) or from 0.25% to 1.07% (mean +/- SD = 0.59 +/- 0.29%) of the maternal dose.