The labels and models used to describe problematic substance use impact discrete elements of stigma: A Registered Report

Objectives: Problematic substance use is one of the most stigmatised health conditions leading research to examine how the labels and models used to describe it influence public stigma. Two recent studies examine whether beliefs in a disease model of addiction influence public stigma but result in equivocal findings – in line with the mixed-blessings model, Kelly et al. (2021) found that whilst the label ‘chronically relapsing brain disease’ reduced blame attribution, it decreased prognostic optimism and increased perceived danger and need for continued care; however, Rundle et al. (2021) conclude absence of evidence. This study isolates the different factors used in these two studies to assess whether health condition (drug use vs. health concern), aetiological label (brain disease vs. problem), and attributional judgement (low vs. high treatment stability) influence public stigma towards problematic substance use. Methods: 1613 participants were assigned randomly to one of eight vignette conditions that manipulated these factors. They completed self-report measures of discrete and general public stigma and an indirect measure of discrimination. Results: Greater social distance, danger, and public stigma but lower blame were ascribed to drug use relative to a health concern. Greater (genetic) blame was reported when drug use was labelled as a ‘chronically relapsing brain disease’ relative to a ‘problem’. Findings for attributional judgement were either inconclusive or statistically equivalent. Discussion: The labels used to describe problematic substance use appear to impact discrete elements of stigma. We suggest that addiction is a functional attribution, which may explain the mixed literature on the impact of aetiological labels on stigma to date

Implementation of child-centred outcome measures in routine paediatric healthcare practice: a systematic review

Background: Person-centred outcome measures (PCOMs) are commonly used in routine adult healthcare to measure and improve outcomes, but less attention has been paid to PCOMs in children’s services. The aim of this systematic review is to identify and synthesise existing evidence of the determinants, strategies, and mechanisms that influence the implementation of PCOMs into paediatric healthcare practice. Methods: The review was conducted and reported in accordance with PRISMA guidelines. Databased searched included CINAHL, Embase, Medline, and PsycInfo. Google scholar was also searched for grey literature on 25th March 2022. Studies were included if the setting was a children’s healthcare service, investigating the implementation or use of an outcome measure or screening tool in healthcare practice, and reported outcomes relating to use of a measure. Data were tabulated and thematically analysed through deductive coding to the constructs of the adapted-Consolidated Framework for Implementation Research (CFIR). Results were presented as a narrative synthesis, and a logic model developed. Results: We retained 69 studies, conducted across primary (n = 14), secondary (n = 13), tertiary (n = 37), and community (n = 8) healthcare settings, including both child self-report (n = 46) and parent-proxy (n = 47) measures. The most frequently reported barriers to measure implementation included staff lack of knowledge about how the measure may improve care and outcomes; the complexity of using and implementing the measure; and a lack of resources to support implementation and its continued use including funding and staff. The most frequently reported facilitators of implementation and continued use include educating and training staff and families on: how to implement and use the measure; the advantages of using PCOMs over current practice; and the benefit their use has on patient care and outcomes. The resulting logic model presents the mechanisms through which strategies can reduce the barriers to implementation and support the use of PCOMs in practice. Conclusions: These findings can be used to support the development of context-specific implementation plans through a combination of existing strategies. This will enable the implementation of PCOMs into routine paediatric healthcare practice to empower settings to better identify and improve child-centred outcomes. Trial registration: Prospero CRD 42022330013

The labels and models used to describe problematic substance use impact discrete elements of stigma: A registered report.

Objectives: Problematic substance use is one of the most stigmatized health conditions leading research to examine how the labels and models used to describe it influence public stigma. Two recent studies examine whether beliefs in a disease model of addiction influence public stigma but result in equivocal findings — in line with the mixed-blessings model, Kelly et al. (2021) found that while the label “chronically relapsing brain disease” reduced blame attribution, it decreased prognostic optimism and increased perceived danger and need for continued care; however,Rundle et al. (2021) conclude absence of evidence. This study isolates the different factors used in these two studies to assess whether health condition (drug use vs. health concern), etiological label (brain disease vs. problem), and attributional judgment (low vs. high treatment stability) influence public stigma toward problematic substance use. Method: Overall, 1,613 participants were assigned randomly to one of the eight vignette conditions that manipulated these factors. They completed self-report measures of discrete and general public stigma and an indirect measure of discrimination. Results: Greater social distance, danger, and public stigma but lower blame were ascribed to drug use relative to a health concern. Greater (genetic) blame was reported when drug use was labeled as a“chronically relapsing brain disease” relative to a “problem”. Findings for attributional judgment were either inconclusive or statistically equivalent. Discussion: The labels used to describe problematic substance use appear to impact discrete elements of stigma. We suggest that addiction is a functional attribution, which may explain the mixed literature on the impact of etiological labels on stigma to date

Formation of Terrestrial Planets

The past decade has seen major progress in our understanding of terrestrial planet formation. Yet key questions remain. In this review we first address the growth of 100 km-scale planetesimals as a consequence of dust coagulation and concentration, with current models favoring the streaming instability. Planetesimals grow into Mars-sized (or larger) planetary embryos by a combination of pebble- and planetesimal accretion. Models for the final assembly of the inner Solar System must match constraints related to the terrestrial planets and asteroids including their orbital and compositional distributions and inferred growth timescales. Two current models -- the Grand-Tack and low-mass (or empty) primordial asteroid belt scenarios -- can each match the empirical constraints but both have key uncertainties that require further study. We present formation models for close-in super-Earths -- the closest current analogs to our own terrestrial planets despite their very different formation histories -- and for terrestrial exoplanets in gas giant systems. We explain why super-Earth systems cannot form in-situ but rather may be the result of inward gas-driven migration followed by the disruption of compact resonant chains. The Solar System is unlikely to have harbored an early system of super-Earths; rather, Jupiter's early formation may have blocked the ice giants' inward migration. Finally, we present a chain of events that may explain why our Solar System looks different than more than 99\% of exoplanet systems

Optimization of adsorptive removal of α-toluic acid by CaO2 nanoparticles using response surface methodology

The present work addresses the optimization of process parameters for adsorptive removal of α-toluic acid by calcium peroxide (CaO2) nanoparticles using response surface methodology (RSM). CaO2 nanoparticles were synthesized by chemical precipitation method and confirmed by Transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) analysis which shows the CaO2 nanoparticles size range of 5–15 nm. A series of batch adsorption experiments were performed using CaO2 nanoparticles to remove α-toluic acid from the aqueous solution. Further, an experimental based central composite design (CCD) was developed to study the interactive effect of CaO2 adsorbent dosage, initial concentration of α-toluic acid, and contact time on α-toluic acid removal efficiency (response) and optimization of the process. Analysis of variance (ANOVA) was performed to determine the significance of the individual and the interactive effects of variables on the response. The model predicted response showed a good agreement with the experimental response, and the coefficient of determination, (R2) was 0.92. Among the variables, the interactive effect of adsorbent dosage and the initial α-toluic acid concentration was found to have more influence on the response than the contact time. Numerical optimization of process by RSM showed the optimal adsorbent dosage, initial concentration of α-toluic acid, and contact time as 0.03 g, 7.06 g/L, and 34 min respectively. The predicted removal efficiency was 99.50%. The experiments performed under these conditions showed α-toluic acid removal efficiency up to 98.05%, which confirmed the adequacy of the model prediction