Our study has some limitations. First, ED visit data might be underestimating the true incidence of non-fatal opioid overdose events as not everyone who experiences an overdose event presents at an ED.
ED data might leave gaps in true incidence level of overdose events, might underestimate responses, important to consider when looking at success in avoiding overdose etc.
Table 3 presents unadjusted and adjusted hazard ratios from the cause-specioc model. After accounting for potential confounding, competing risks, and individual-level random effects, we observed that in-jail MOUD was associated with reduced risk of non-fatal opioid
Important to note that this doesn't indicate that half of people avoided overdose completely, simply the reduced risk was around this figure for this certain group.
The null association between in-jail MOUD and non-fatal overdose after the orst two weeks post-jail release in our study may renect chal- lenges in accessing and continuing care at OTPs
Note for my potential policy idea/reform: importance of continued care and access, expanding resources for victims and OTPs.
Based on the observed SMD, we concluded there were important imbalances between the out-of-treatment and MOUD groups with respect to a number of characteristics.
Groups differed on several characteristics, potentially influencing results. Important to adjust for these differences, otherwise we might want to take results with a grain of salt.
Unlike the orst 2 weeks, we found no associations within 15–28, 29–56, or 57–365 days after release
No significant associations found in later periods, potential need for better continued help etc?
2.7. Covariates
It appears they accounted for a lot of factors that might've influence their data/overdose risk. Adjusting for these would strengthen results, but important to note that all confounding variables cannot be accounted for.
Fig. 1
31,382 incarceration events, not 31,382 individual people, important to note repeat incarcerations/movement.
p.
Couldn't annotate on p2, felt it was important to note the authors mentioning of the lack of studies on this kind of subject, particularly the part about overdoses after jail release, which I took to mean that this study could be important for shaping policy.
r non-fatal opioid overdose risk
For some reason I couldn't annotate on page 2, but I felt that looking at nonfatal overdoses is important because it can help protect from potentially deadly overdoses, but also can cause harm to the victims that lasts with them throughout life. If they just looked at deadly overdoses, they might miss key analysis and data.
Although drug addiction is a chronic medical condition requiring a public health approach to reduce harm, it continues to be criminalized
The authors talk about how OUD is a medical condition while also mentioning the fact that it is criminalized, so I am felt like this sort of tied into my initial research questions, specifically what big picture ideas etc. are affected/undermined by punishing these people without helping treat them.
the risk of experiencing an overdose is highest when transitioning from a correctional setting to the community.
I found this fact really interesting, because I had never before considered this type of spike in danger associated with a change of environment. I'm curious whether the policies involved with these facilities are helping to reduce this danger, or actively making it worse.
Limitations.
Important to note the small sample size, as well as the similarity/unrepresentativeness of participants compared to general population, as this might not help bring about discoveries surrounding people with alcoholism or more elderly drinkers, just to name a few groups.
Compared to pre-beverage functional connectivity, placebo beverage was associated with increased functional connectivity in a cluster of connections between right NAcc with vmPFC and SCC [F(3,19)= 10.1, pFDR= 0.005]. Post-hoc connection-level comparisons indicated the right NAcc showed increased functional connectivity with vmPFC [t[21]= 3.3, pFDR= 0.04, r2 = 0.11] and SCC [t[21]= 3.1, pFDR= 0.04, r2 = 0.13] following placebo beverage, compared to pre-beverage func- tional connectivity. R
Importance of results indicating serious changes in brain function accompanied with placebo, related to higher ratings, but would be careful to establish causation.
Table 2 Subjective response before and after placebo beverage consumption.
Table: all three categories of subjective ratings rose significantly after the placebo was administered, despite 0 rise in their BrAC levels. This showcases the power of perception and the effects it has on people.
Methods:
IV: Participants measures before and after consumption DVs: Changes in resting state functional connectivity, changes in subjective intoxication, etc.
Associations between subjective response with functional connectivity response to placebo beverage
Important to note difference between participant ratings vs researchers examining changes in functional connectivity
he video depicts an inan- imate object changing shape and has been used successfully in resting state fMRI studies [32]. Differences in functional connectivity while viewing the Inscapes video, compared to more traditional resting state paradigms (when participant views a fixation point), have been reported [32]; hence this study may not necessarily be capturing the brain “at rest”.
Are they really in a resting state if they're forced to watch a video? The authors acknowledge this, but I wonder what effects it had on the results (type of brain activity)
e repeated BrAC testing after completion of beverage consumption (post-beverage) to enhance believability of the placebo manipulation. We timed post- beverage BrAC measurement collection during the placebo to be iden- tical to timing of BrAC measurement collection during an alcohol session (which is collected 10 min following completion of beverages to allow for a 10-minute absorption period).
There doesn't seem to be a separate no-beverage control (within-subjects), note independent comparison, can't completely isolate expectancy from other factors
Twenty-six healthy young adults (ages 21 – 26 years) enrolled in the
Methods: 26 enrolled, ended with N = 22 of 21-26 year old adults.
0.000.
BrAC was guaranteed to be at 0, which is important because it eliminates possibility that some of the reported drunkenness was from actual consumption of alcohol.
We hypothe- sized placebo beverage consumption would be associated with an increase in resting state functional connectivity within prefrontal cortical (PFC) networks—including PFC, ACC, amygdala, insula, and striatum—that govern reward and emotion processes.
Hypothesis: placebo consumption will increase connectivity in prefrontal and reward areas, and that an increase in connectivity within these areas will lead to higher individual ratings of intoxication.
The data reported here were obtained from a larger study design using within-subjects placebo-controlled alcohol administration methods to investigate sub- jective and neural response to alcohol
This study is different in the sense that it doesn't do this, but instead primarily looks at the placebo effects of alcohol instead of comparing alcohol vs placebo.
Background:
Research question: Is it possible that believing one consumed alcohol influence reward-network communication/connectivity, even when no alcohol was consumed? This research questions expands on traditional studies that only look at perceived alcohol consumption's effects on behaviors