Racial matching and adolescent self-disclosure of substance use and mental health symptoms

Obtaining accurate assessment data from adolescents in treatment aids clinical decision making and facilitates more accurate outcome evaluations. However, findings could be biased due to underreported substance use and mental health symptoms. This article compares self-reports of youth in non-White matched client–assessor dyads and those in nonmatched dyads. There were no differences on self-reported substance use, but matched youth reported significantly fewer attention deficit/hyperactivity disorder symptoms versus the comparison group. One possible reason for these findings is the effect of in-group stereotype threat. Future studies should examine the potential effect that in-group stereotyping and perceived racism have on the therapeutic relationship.     

Measuring disease activity and response to treatment in rheumatoid arthritis

Introduction: Effective treatment of rheumatoid arthritis (RA) requires suppression of the underlying inflammation. Measurement of such inflammation, the disease activity, is mandatory to target treatment and maximize outcomes. However, this is not as straightforward as it may seem.

Areas covered: The many tools developed to measure disease activity in RA, from composite scores and patient-reported outcomes, to laboratory markers and imaging are discussed, with a focus on their utility in guiding therapy and assessing response. The complex issues in measuring disease activity in RA, whether in clinical trials or normal clinical practice, and in the context of national guidelines and recommendations, available time, and resources are considered.

Expert commentary: The key to effective management of RA is the rapid suppression of inflammation, ideally to remission, with maintenance of such remission. The aim is to prevent disability and maximize quality of life. Central to this is the ability to determine disease activity (potentially open to suppression) as opposed to damage (irreversible). A variety of measures are currently available, allowing better assessment of response to treatment. In the future, the development of predictive biomarkers allowing targeting of drugs may revolutionize this field and render the tools of today redundant.     

Development of a Simulation-Based Mastery Learning Curriculum for Breaking Bad News

Introduction

Physician communication impacts patient outcomes. However, communication skills, especially around difficult conversations, remain suboptimal, and there is no clear way to determine the validity of entrustment decisions. The aims of this study were to 1) describe the development of a simulation-based mastery learning (SBML) curriculum for breaking bad news (BBN) conversation skills and 2) set a defensible minimum passing standard (MPS) to ensure uniform skill acquisition among learners.

Derivation of internal dose-based thresholds of toxicological concern for occupational inhalation exposure to systemically acting organic chemicals

This study aimed at deriving occupational thresholds of toxicological concern for inhalation exposure to systemically-acting organic chemicals using predicted internal doses. The latter were also used to evaluate the quantitative relationship between occupational exposure limit and internal dose. Three internal dose measures were identified for investigation: (i) the daily area under the venous blood concentration vs. time curve, (ii) the daily rate of the amount of parent chemical metabolized, and (iii) the maximum venous blood concentration at the end of an 8-hr work shift. A dataset of 276 organic chemicals with 8-hr threshold limit values-time-weighted average was compiled along with their molecular structure and Cramer classes (Class I: low toxicity, Class II: intermediate toxicity, Class III: suggestive of significant toxicity). Using a human physiologically-based pharmacokinetic model, the three identified dose metrics were predicted for an 8-hr occupational inhalation exposure to the threshold limit value for each chemical. Distributional analyses of the predicted dose metrics were performed to identify the percentile values corresponding to the occupational thresholds of toxicological concern. Also, simple linear regression analyses were performed to evaluate the relationship between the 8-hr threshold limit value and each of the predicted dose metrics, respectively. No threshold of toxicological concern could be derived for class II due to few chemicals. Based on the daily rate of the amount of parent chemical metabolized, the proposed internal dose-based occupational thresholds of toxicological concern were 5.61?×?10^?2 and 9?×?10^?4 mmol/d at the 10th percentile level for classes I and III, respectively, while they were 4.55?×?10^?1 and 8.5?×?10^?3 mmol/d at the 25th percentile level. Even though high and significant correlations were observed between the 8-hr threshold limit values and the predicted dose metrics, the one with the rate of the amount of chemical metabolized was remarkable regardless of the Cramer class (r² = 0.81; n = 276). The proposed internal dose-based occupational thresholds of toxicological concern are potentially useful for screening-level assessments as well as prioritization within an integrated occupational risk assessment framework.     

Children's diets,pesticide uptake,and implications for risk assessment: An Israeli case study

The presence of pesticides in the Israeli food supply is well documented but little is known about the risks posed by children's diets for potential exposures. We investigated potential exposures to food-borne pesticides in a sample of 301 urban Israeli children (2008–10). Data from a food frequency questionnaire, 24 hour food recall, and Israel's national pesticide monitoring program were used to estimate uptake factors for 26 compounds in 27 fruits and vegetables. A pilot risk assessment was performed and the findings were compared with the Israel Ministry of Health's 2012 pesticide risk assessment for the general population. The surveyed children had higher potential exposures than the general population for over one third of the compounds, and uptake factors exceeded the Acceptable Daily Intake in ten compounds. Methamidophos, exceeded the ADI at the 25th percentile and fenamiphos, iprodione, and oxydemethon methyl, exceeded the ADI at the 50 percentile. ADIs for several compounds were exceeded even though the residues detected were below the statutory limit. Improved monitoring, enforcement, and revision of the Maximum Residue Limit for certain food/pesticide pairs are indicated as is the need to incorporate data on children's actual food consumption in national risk assessments.     

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.