Abstract
The stigma surrounding individuals who have substance use disorders is a pervasive phenomenon that has had detrimental effects on treatment outcomes, health care providers, treatments, ...research, policies, and society as a whole (Kelly JF, Dow SJ, Westerhoff C , J Drug Issues_40:805-818, Kelly JF, Westerhoff, Int J Drug Policy_21:202-207, 2010). Stigma can be cultivated by various sources, but this article specifically focuses on the impact words have. Individuals influence each other through dynamic language processes. Language, which we use to communicate, represents shared values, history, beliefs, and customs. Moreover, language can be used to promote stigma or decrease it Snodgrass S: The Power of Words: Changing the Language of Addiction, 2920. Language usage for addiction medical care is dated in comparison to other standards. Research and organizations are recognizing that substance use treatment, policies, and language need to evolve to aid this crisis and those affected by this disease. Language sustains the stigma surrounding substance use. The stigmatized language used to describe substance use behaviors, individuals with substance use disorders, and substance use treatment can create barriers in essential areas, such as health care, employment, insurance policies, and laws for individuals who are trying to heal and make meaningful contributions to society. There are many ways to contribute to a more accepting society, but it starts with bottom-up processes like language choices in day-to-day conversations. An effort must be made to normalize destigmatized language when referring to substance use and individuals with substance use disorders.
There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. ...Super learning (SL) is a methodology that facilitates this decision by combining all identified prediction algorithms pertinent for a particular prediction problem. SL generates a final model that is at least as good as any of the other models considered for predicting the outcome. The overarching aim of this work is to introduce SL to analysts and practitioners. This work compares the performance of logistic regression, penalized regression, random forests, deep learning neural networks, and SL to predict successful substance use disorders (SUD) treatment. A nationwide database including 99,013 SUD treatment patients was used. All algorithms were evaluated using the area under the receiver operating characteristic curve (AUC) in a test sample that was not included in the training sample used to fit the prediction models. AUC for the models ranged between 0.793 and 0.820. SL was superior to all but one of the algorithms compared. An explanation of SL steps is provided. SL is the first step in targeted learning, an analytic framework that yields double robust effect estimation and inference with fewer assumptions than the usual parametric methods. Different aspects of SL depending on the context, its function within the targeted learning framework, and the benefits of this methodology in the addiction field are discussed.
To see whether the percentage of older adults entering substance abuse treatment for their first time was increasing and whether there were changes in the use patterns leading to the treatment ...episode, particularly an increase in illicit drugs.
The Treatment Episode Data Sets publicly available from the Substance Abuse Mental Health Services Administration from 1998 to 2008.
Young adults age 30-54 years as a comparison group (N = 3,547,733) and those age 55 years or older (N = 258,542) with a first-time admission for a publicly funded substance abuse treatment.
Demographic and substance use history variables at admission.
The proportion of older adults going for substance abuse treatment for the first time is increasing relative to younger adults. The pattern of drug use is also changing, with an increasing illicit drug involvement (cocaine and heroin) in older adult admissions.
We know little of these long-time users, their current medical state, cognitive abilities, and psychiatric symptoms after such a long exposure time. Previous studies on heroin and cocaine exposure focused on individuals identified much earlier in life, and the aging long-term users might represent a relatively large but unknown population.
Practice effects on cognitive tests have been shown to further characterize patients with amnestic mild cognitive impairment (aMCI) and may provide predictive information about cognitive change ...across time. We tested the hypothesis that a loss of practice effects would portend a worse prognosis in aMCI.
Longitudinal, observational design following participants across 1 year.
Community-based cohort.
Three groups of older adults: 1) cognitively intact (n = 57), 2) aMCI with large practice effects across 1 week (MCI + PE, n = 25), and 3) aMCI with minimal practice effects across 1 week (MCI - PE, n = 26).
Neuropsychological tests.
After controlling for age and baseline cognitive differences, the MCI - PE group performed significantly worse than the other groups after 1 year on measures of immediate memory, delayed memory, language, and overall cognition.
Although these results need to be replicated in larger samples, the loss of short-term practice effects portends a worse prognosis in patients with aMCI.
Newborn admission to the neonatal intensive care unit (NICU) is stressful. Yet in clinical practice, at best, NICU mothers are screened for depression and if indicated, referred to a mental-health ...specialist. At worst, no action is taken. Listening Visits, an empirically supported nurse-delivered intervention addressing emotional distress, can be conveniently provided by a NICU nurse. Prompted by the need to minimize face-to-face contacts during the pandemic, the primary purpose of this small pilot trial was to assess the feasibility of having nurses provide Listening Visits to NICU mothers over Zoom. Secondarily, we assessed pre-to post-Listening Visits depression symptom scores as a preliminary evaluation of the effectiveness of this type of support.
Nine NICU mothers with mildly to moderately severe depression symptoms received up to six Listening Visits sessions from a NICU nurse via Zoom. Participants completed the Inventory Depression and Anxiety Symptoms-General Depression scale (IDAS-GD) at study entry and 4- and 8-weeks post enrollment. They completed the Client Satisfaction Questionnaire (CSQ) at the 8-week assessment.
Using an intent-to-treat approach, the effect of time from the mixed model analysis of IDAS-GD was statistically significant (
(2,26) = 10.50,
< 0.001), indicating improvement in IDAS-GD scores from baseline to follow-up. The average CSQ score was high (
= 29.0, SD = 3.3), with 75% of participants rating the quality of help they received as "excellent".
In this pilot trial, we learned it is feasible to provide Listening Visits over Zoom, that this mode of delivery is associated with a significant decrease in depression symptom scores, and that women value this approach.
https://clinicaltrials.gov/, identifier #201805961.
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