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Cannabis Use Disorder and Treatment
Published in James M. Rippe, Lifestyle Medicine, 2019
Christina Aivadyan, Deborah Hasin
As attitudes and laws about cannabis use evolve and the prevalence of cannabis use increases, healthcare providers, policymakers, and the general public need to be aware of the risks associated with cannabis use. Clinicians should screen and assess all patients for cannabis use and cannabis-related problems, inform cannabis users of potential adverse consequences of use, and refer those with CUD to treatment. Additionally, further research is needed to:1.Identify risk factors for adverse cannabis-related outcomes and changes in such risk factors amid a changing legal and social landscape.2.Further develop screening and assessment tools to detect cannabis use and cannabis-related problems, including CUD.3.Provide information on the efficacy of interventions aimed at increasing awareness of cannabis risks and reducing use, particularly among those with a higher likelihood of adverse consequences.4.Understand the rel ationships between cannabis use and cognitive functioning, cannabis withdrawal and psychiatric disorders, opioid use and marijuana laws (both for medical and recreational use), and postnatal outcomes related to using cannabis during pregnancy.
Quality of Life
Published in Satrajit Roychoudhury, Soumi Lahiri, Statistical Approaches in Oncology Clinical Development, 2018
If all of the patients in the study have been followed up to death, finding the average time in each health state is quite easy as the time for each is known for every patient. But when there is censoring, we need to use methods developed for survival analyses. Figure 9.5 illustrates the Kaplan–Meier estimates for the time to the end of treatment (TOX), the end of the disease-free survival (DFS), and the end of survival (SURV) for the patients an adjuvant breast cancer trial with up to 60 months of follow-up. The average time in TOX is equal to the AUC for the time to the end of treatment. The heath state TWiST is defined as the time between the end of TOX and DFS. The average time spent in TWiST is equal to the area between the two curves. Similarly, the health state REL is defined as the time between the end of DFS and SURV. The average time in REL is again the area between the curves. When the follow-up is incomplete, we must estimate restricted means that estimate the average times in each health state up to a set limit. At the first glance, it might appear that 60 months (five years) would be a good choice. However, for practical reasons related to the estimation of the variance of the estimates, it is more appropriate to pick a time where follow-up is complete for 50%–75% of the subjects who are still being followed.
Case Study
Published in George Engelhard, Stefanie A. Wind, Invariant Measurement with Raters and Rating Scales, 2017
George Engelhard, Stefanie A. Wind
It is also possible to explore differences in reliability related to unique facets in a measurement procedure within the framework of Rasch Measurement Theory using reliability estimates based on the MF model. The underlying reliability concerns related to this facet can be summarized using the following question: What is the reliability/precision of rater judgments related to various cues? Reliability indices based on the Rasch model can be calculated separately for each facet in the model. Two indices of reliability are typically used: (1) reliability of separation (Rel) and (2) a chi-square statistic (x2).
Identification of disease genes and assessment of eye-related diseases caused by disease genes using JMFC and GDLNN
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Samar Jyoti Saikia, S. R. Nirmala
The initial process is the SS computation of genes. For this procedure, initially, the genes are amassed as of the openly available database. Subsequent to gathering genes, the SS is computed for the inputted genes to recognize whether it is an animal gene or a human gene. Aimed at this, GO is utilized. GO is basically a structured and also controlled vocabulary of terms to illustrate gene products. GO is organized as a directed acyclic graph (DAG) wherein terms are denoted as nodes along with relationships betwixt the disparate terms are indicated as edges (Liu et al. 2018). The effortlessness of searching together with richness in biological details has made GO an imperative resource for studying gene characteristics. For building functional similarity matrices aimed at genes along with non-disease genes, Resnik (Ren et al. 2020), Wang, as well as Relevance (Rel) (Mazandu et al. 2016) semantic similarity with Maximum (Max) joining strategy (Schmoldt et al. 1975) were employed. Rel and Resnik are information content (IC)-centered measures. IC-centered methods calculate a semantic score betwixt the ‘2’ GO terms utilizing the IC of their most informative commons ancestors (MICA) term. Let
2021–2022 Southern Illinois University National Health Law Moot Court Competition
Published in Journal of Legal Medicine, 2021
Cheryl L. Anderson, Schuyler Frashier, Abigael Schulz
In order to state a claim under the FCA, Mason only needed to assert that a physician’s certification that HBO therapy was “medically necessary” was false or fraudulent for the same reasons that any opinion can be false or fraudulent. Mason alleged facts that, if true, demonstrate that the treatments for which SAM Clinics sought reimbursement were improperly certified as medically necessary. She provided a qualified medical expert who concluded that HBO therapy was not medically necessary for the identified patients. If that difference in medical opinion about medical necessity is enough to create a jury question, it is enough to survive a motion to dismiss. Cf. United States ex rel Druding v. Care Alternatives, 952 F.3d 89, 98 (3d Cir. 2020) (concluding that a jury can consider whether a certification of medical necessity was false based on an expert’s testimony challenging the certifying physician’s medical opinion). Mason had more than merely a difference in medical opinion; she also had other information about a scheme to intentionally defraud Medicare by performing medically unnecessary treatments. She had shown a plausible claim under the FCA and the lower court should have denied the motion to dismiss.
Are You Ready to Have Fun? The Spanish State Form of the State–Trait–Cheerfulness Inventory
Published in Journal of Personality Assessment, 2019
Raúl López-Benítez, Alberto Acosta, Juan Lupiáñez, Hugo Carretero-Dios
This variance decomposition enables us to establish three coefficients that are the most important values in all LST studies: the consistency (CO), the occasion specificity (OSpe), and the reliability (Rel) coefficients (for more detailed information about the LST coefficients, see Geiser et al., 2015). CO indicates the degree to which individual differences in the observed variables are determined by stable person-specific (trait) effects. The larger the CO values, the less the scores vary over specific situations or assessment points. OSpe stands for the proportion of variance determined by the interaction of situation and state. The larger the OSpe values, the stronger the impact of situation-specific or Person × Situation interaction variability on the observed scores. Rel is the sum of the CO and the OSpe indicators, reflecting the degree to which observed individual differences are not due to measurement error.