A First-Tier Framework for Assessing Toxicological Risk from Vaporized Cannabis Concentrates

Vaporization is an increasingly prevalent means to consume cannabis, but there is little guidance for manufacturers or regulators to evaluate additive safety. This paper presents a first-tier framework for regulators and cannabis manufacturers without significant toxicological expertise to conduct risk assessments and prioritize additives in cannabis concentrates for acceptance, elimination, or further evaluation. Cannabinoids and contaminants (e.g., solvents, pesticides, etc.) are excluded from this framework because of the complexity involved in their assessment; theirs would not be a first-tier toxicological assessment. Further, several U.S. state regulators have provided guidance for major cannabinoids and contaminants. Toxicological risk assessment of cannabis concentrate additives, like other types of risk assessment, includes hazard assessment, dose–response, exposure assessment, and risk characterization steps. Scarce consumption data has made exposure assessment of cannabis concentrates difficult and variable. Previously unpublished consumption data collected from over 54,000 smart vaporization devices show that 50th and 95th percentile users consume 5 and 57 mg per day on average, respectively. Based on these and published data, we propose assuming 100 mg per day cannabis concentrate consumption for first-tier risk assessment purposes. Herein, we provide regulators, cannabis manufacturers, and consumers a preliminary methodology to evaluate the health risks of cannabis concentrate additives

The development of a nursing subset of patient problems to support interoperability

Since the emergence of electronic health records, nursing information is increasingly being recorded and stored digitally. Several studies have shown that a wide range of nursing information is not interoperable and cannot be re-used in different health contexts. Difficulties arise when nurses share information with others involved in the delivery of nursing care. The aim of this study is to develop a nursing subset of patient problems that are prevalent in nursing practice, based on the SNOMED CT terminology to assist in the exchange and comparability of nursing information. Explorative qualitative focus groups were used to collect data. Mixed focus groups were defined. Additionally, a nursing researcher and a nursing expert with knowledge of terminologies and a terminologist participated in each focus group. The participants, who work in a range of practical contexts, discussed and reviewed patient problems from various perspectives. Sixty-seven participants divided over seven focus groups selected and defined 119 patient problems. Each patient problem could be documented and coded with a current status or an at-risk status. Sixty-six percent of the patient problems included are covered by the definitions established by the International Classification of Nursing Practice, the reference terminology for nursing practice. For the remainder, definitions from either an official national guideline or a classification were used. Each of the 119 patient problems has a unique SNOMED CT identifier. To support the interoperability of nursing information, a national nursing subset of patient problems based on a terminology (SNOMED CT) has been developed. Using unambiguously defined patient problems is beneficial for clinical nursing practice, because nurses can then compare and exchange information from different settings. A key strength of this study is that nurses were extensively involved in the development process. Further research is required to link or associate nursing patient problems to concepts from a nursing classification with the same meaning

Functional assessment of school attendance problems: An adapted version of the School Refusal Assessment Scale-Revised

Pathways through Adolescenc

A simple predictive model for estimating relative e-cigarette toxic carbonyl levels.

E-cigarette devices are wide ranging, leading to significant differences in levels of toxic carbonyls in their respective aerosols. Power can be a useful method in predicting relative toxin concentrations within the same device, but does not correlate well to inter-device levels. Herein, we have developed a simple mathematical model utilizing parameters of an e-cigarette's coil and wick in order to predict relative levels of e-liquid solvent degradation. Model 1, which is coil length/(wick surface area*wraps), performed in the moderate-to-substantial range as a predictive tool (R2 = 0.69). Twelve devices, spanning a range of coil and wick styles, were analyzed. Model 1 was evaluated against twelve alternative models and displayed the best predictability. Relationships that included power settings displayed weak predictability, validating that power levels cannot be reliably compared between devices due to differing wicking and coil components and heat transfer efficiencies