Policies for Tobacco and E-Cigarette Use: A Survey of All Higher Education Institutions and NHS Trusts in England.

INTRODUCTION: There is an absence of evidence regarding the impact of treating tobacco smoking and vaping equivalently in workplace policies. We aimed to describe and compare smoking and vaping policies in acute nonspecialist NHS Trusts (n = 131) and Higher Education Institutions (HEIs) (n = 131) in England. METHODS: We conducted a census of smoking and vaping policies through organizational websites searches and direct requests for information. We recorded whether and where smoking and vaping were permitted. RESULTS: Smoking was prohibited indoors in all organizations. No NHS Trust permitted smoking freely outdoors, in contrast with 60% of HEIs. In 27% of NHS Trusts and 33% of HEIs smoking was permitted in designated areas, while in 73% of NHS Trusts and 8% of HEIs smoking was prohibited anywhere on site. Vaping was prohibited indoors in all NHS Trusts and all but one HEI, but permitted freely outdoors in 18% of NHS Trusts and 75% of HEIs. Vaping was permitted in designated outdoor spaces in 23% of NHS Trusts: 21% had areas shared with smokers; 2% had separate vaping areas. Vaping was permitted in designated outdoor areas in 18% of HEIs, all of which were shared with smokers. Vaping was prohibited anywhere on site in 54% of NHS Trusts and 6% of HEIs. CONCLUSIONS: Policies vary considerably in whether vaping and smoking are treated equivalently. Smoking policies in most HEIs should be reviewed to include more effective tobacco control approaches. Evidence is needed on the impact of imposing shared or separate spaces on vapers and smokers. IMPLICATIONS: This report provides a comprehensive review of smoking and vaping policies in two types of organization across England. It highlights key discrepancies between current public health recommendations for vaping and existing workplace policies, which often lead to smokers and vapers sharing spaces. The report identifies the need for evidence on the impact of imposing shared spaces on smokers and vapers to inform workplace policies that maximize public health benefit

Size matters but when, why and for whom?

Pack size of tobacco products, including factory-made cigarettes and loose tobacco, is an important but neglected aspect of tobacco control policy. Understanding the nature of the relationship between pack size and consumption, as well as the underlying mechanisms, is key for informing effective policy and reducing smoking prevalenc

Impact of e-cigarette retail displays on attitudes to smoking and vaping in children: an online experimental study

OBJECTIVES: To estimate the impact of electronic cigarette (e-cigarette) retail display exposure on attitudes to smoking and vaping (susceptibility to tobacco smoking and using e-cigarettes, and perceptions of the harms of smoking and e-cigarette use). DESIGN: Between-subjects randomised experiment using a 2 (e-cigarette retail display visibility: high vs low)×2 (proportion of e-cigarette images: 75% vs 25%) factorial design. SETTING: Online via the Qualtrics survey platform. PARTICIPANTS: UK children aged 13-17 years (n=1034), recruited through a research agency. INTERVENTION: Participants viewed 12 images of retail displays that contained e-cigarette display images or unrelated product images. E-cigarette display images were either high or low visibility, based on a conspicuousness score. Participants were randomised to one of four groups, with e-cigarette display visibility and proportion of e-cigarette images, compared with images of unrelated products, manipulated: (1) 75% e-cigarettes, high visibility; (2) 25% e-cigarettes, high visibility; (3) 75% e-cigarettes, low visibility; (4) 25% e-cigarettes, low visibility. MAIN OUTCOME MEASURES: The primary outcome was susceptibility to smoking (among never smokers only). Secondary outcomes were susceptibility to using e-cigarettes (among never vapers only), and perceptions of smoking and e-cigarette harm (all participants). RESULTS: Neither e-cigarette retail display visibility, nor the proportion of e-cigarette images displayed, appeared to influence susceptibility to smoking (visibility: OR=0.84, 95% CI 0.62 to 1.13, p=0.24; proportion: OR=1.34, 95% CI 1.00 to 1.82, p=0.054 (reference: low visibility, not susceptible)).Planned subgroup analyses indicated that exposure to a higher proportion of e-cigarette images increased susceptibility to smoking among children who visited retail stores more regularly (n=524, OR=1.59, 95% CI 1.04 to 2.43, p=0.034), and those who passed the attention check (n=880, OR=1.43, 95% CI 1.03 to 1.98, p=0.031).In addition, neither e-cigarette retail display visibility nor the proportion of e-cigarette images displayed, appeared to influence susceptibility to using e-cigarettes (visibility: OR=1.07, 95% CI 0.80 to 1.43, p=0.65; proportion: OR=1.22, 95% CI 0.91 to 1.64, p=0.18).Greater visibility of e-cigarette retail displays reduced perceived harm of smoking (mean difference (MD)=-0.19, 95% CI -0.34 to -0.04, p=0.016). There was no evidence that the proportion of e-cigarette images displayed had an effect (MD=-0.07, 95% CI -0.22 to 0.09, p=0.40).Perceived harm of e-cigarette use did not appear to be affected by e-cigarette retail display visibility (MD=-0.12, 95% CI -0.28 to 0.05, p=0.16) or by the proportion of e-cigarette images displayed (MD=-0.10, 95% CI -0.26 to 0.07, p=0.24). CONCLUSIONS: There is no evidence in the full sample to suggest that children's susceptibility to smoking is increased by exposure to higher visibility e-cigarette retail displays, or to a higher proportion of e-cigarette images. However, for regular store visitors or those paying more attention, viewing a higher proportion of e-cigarette images increased susceptibility to smoking. In addition, viewing higher visibility e-cigarette images reduced perceived harm of smoking. A review of the current regulatory discrepancy between tobacco and e-cigarette point-of-sale marketing is warranted. TRIAL REGISTRATION NUMBER: ISRCTN18215632

IntEgrating Smoking Cessation treAtment into usual online Psychological care for people with common mEntal illness: Protocol for an online randomised feasibility and pilot study (ESCAPE digital)

Background In the UK, smoking prevalence in people with depression (34%) and anxiety (29%) is more than double that of the general population (13%). People who stop smoking improve their mental health with comparable effect sizes found for antidepressants. In England, online psychological therapy is a standard treatment for depression and anxiety. Online therapy is an acceptable setting for smoking cessation support; however, integrated smoking and mental health support is not available. This novel study aims to assess the acceptability and feasibility of an online smoking cessation intervention, and trial procedures, offered alongside online mental health treatment as it offers increased reach to people with common mental health difficulties who smoke. Methods A two-armed; Intervention (Integrated SilverCloud smoking cessation support) and control group (SilverCloud usual care), pragmatic, randomised controlled feasibility trial. We aim to recruit 500 adult smokers eligible for online mental health treatment. Follow-up will be conducted at 3-months and 6-months. We will assess the acceptability and feasibility of the trial procedures (i.e., recruitment, data completeness, self-reported acceptability and satisfaction) and the intervention (i.e., self-reported quit attempt, engagement with the smoking cessation and mental health programs, smoking cessation medicine and e-cigarette use, self-reported acceptability and satisfaction) and pilot clinical outcomes (i.e., biologically validated smoking abstinence, anxiety, depression, quality of health). Conclusion If the Trial is successful, a randomised controlled effectiveness trial will follow to examine whether integrated smoking cessation and mental health treatment increases smoking abstinence and improves depression and anxiety compared to usual care. Trial registration: ISRCTN10612149 (https://doi.org/10.1186/ISRCTN10612149), 02/02/2023

Multizone Paper Platform for 3D Cell Cultures

In vitro 3D culture is an important model for tissues in vivo. Cells in different locations of 3D tissues are physiologically different, because they are exposed to different concentrations of oxygen, nutrients, and signaling molecules, and to other environmental factors (temperature, mechanical stress, etc). The majority of high-throughput assays based on 3D cultures, however, can only detect the average behavior of cells in the whole 3D construct. Isolation of cells from specific regions of 3D cultures is possible, but relies on low-throughput techniques such as tissue sectioning and micromanipulation. Based on a procedure reported previously (“cells-in-gels-in-paper” or CiGiP), this paper describes a simple method for culture of arrays of thin planar sections of tissues, either alone or stacked to create more complex 3D tissue structures. This procedure starts with sheets of paper patterned with hydrophobic regions that form 96 hydrophilic zones. Serial spotting of cells suspended in extracellular matrix (ECM) gel onto the patterned paper creates an array of 200 micron-thick slabs of ECM gel (supported mechanically by cellulose fibers) containing cells. Stacking the sheets with zones aligned on top of one another assembles 96 3D multilayer constructs. De-stacking the layers of the 3D culture, by peeling apart the sheets of paper, “sections” all 96 cultures at once. It is, thus, simple to isolate 200-micron-thick cell-containing slabs from each 3D culture in the 96-zone array. Because the 3D cultures are assembled from multiple layers, the number of cells plated initially in each layer determines the spatial distribution of cells in the stacked 3D cultures. This capability made it possible to compare the growth of 3D tumor models of different spatial composition, and to examine the migration of cells in these structures

Notes for genera: basal clades of Fungi (including Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota)

Compared to the higher fungi (Dikarya), taxonomic and evolutionary studies on the basal clades of fungi are fewer in number. Thus, the generic boundaries and higher ranks in the basal clades of fungi are poorly known. Recent DNA based taxonomic studies have provided reliable and accurate information. It is therefore necessary to compile all available information since basal clades genera lack updated checklists or outlines. Recently, Tedersoo et al. (MycoKeys 13:1--20, 2016) accepted Aphelidiomycota and Rozellomycota in Fungal clade. Thus, we regard both these phyla as members in Kingdom Fungi. We accept 16 phyla in basal clades viz. Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. Thus, 611 genera in 153 families, 43 orders and 18 classes are provided with details of classification, synonyms, life modes, distribution, recent literature and genomic data. Moreover, Catenariaceae Couch is proposed to be conserved, Cladochytriales Mozl.-Standr. is emended and the family Nephridiophagaceae is introduced

The impact on selection of non-alcoholic vs alcoholic drink availability: an online experiment.

BACKGROUND: Increasing the availability of healthier food increases its selection and consumption. However, there is an absence of evidence related to alcohol. This study aimed to estimate the impact of increasing the absolute and relative availability of non-alcoholic compared to alcoholic drinks on selection. We also assessed whether effects were modified by cognitive resource. METHODS: UK adult weekly alcohol consumers (n = 808) were recruited to an online experiment with a hypothetical drink selection task. Participants were randomly assigned to one of eight conditions, in a 4 (availability) × 2 (cognitive resource) factorial design. The four availability conditions were: i. Reference 1 (two non-alcoholic, two alcoholic drinks); ii. Reference 2 (four non-alcoholic, four alcoholic drinks); iii. Increased non-alcoholic drinks (six non-alcoholic, two alcoholic drinks); iv. Increased alcoholic drinks (two non-alcoholic, six alcoholic drinks). The two cognitive resource conditions were: a. Low (high time pressure); b. High (low time pressure). Logistic regression was used to assess selection of a non-alcoholic drink. RESULTS: 49% of participants selected a non-alcoholic drink in the Increased non-alcoholic drinks condition, compared to 36% in Reference 1, 39% in Reference 2, and 26% in the Increased alcoholic drinks condition. Non-alcoholic drink selection was similar between Reference 1 and 2 when the total number of drinks increased (absolute availability) but the proportion of non-alcoholic compared to alcoholic drinks (relative availability) was unchanged (OR = 1.15, 95% CI 0.77, 1.73). In contrast, the odds of selecting a non-alcoholic drink were 71% higher when both absolute and relative availability of non-alcoholic compared to alcoholic drinks was increased from Reference 1 to the Increased non-alcoholic drinks condition (OR: 1.71, 95% CI 1.15, 2.54), and 48% higher when increased from Reference 2 to the Increased non-alcoholic drinks condition (OR: 1.48, 95% CI 0.99, 2.19). There was no evidence of an effect of cognitive resource. CONCLUSIONS: Greater availability of non-alcoholic drinks, compared to alcoholic drinks, increased their online selection, an effect that may be larger when changing their relative availability, i.e., increasing the proportion of non-alcoholic drinks. Naturalistic studies are needed to determine the impact of availability interventions on reducing alcohol purchasing and consumption

Tobacco and electronic cigarette cues for smoking and vaping: an online experimental study.

OBJECTIVE: This study examined whether exposure to smoking and vaping cues the urge to smoke or vape. It extends previous studies on first-generation cigalikes (visually similar to cigarettes) and second-generation devices (visually similar to pens) by including third-generation tank system devices (larger bulky units). In an online experiment, participants were randomly assigned to view one of four videos, which included smoking, vaping (cigalike or tank system), or neutral cues. The primary outcome was urge to smoke. Secondary outcomes were urge to vape, desire to smoke and vape, and intention to quit or remain abstinent from smoking. RESULTS: UK adults varying in smoking (current or former) and vaping (user or non-user) status (n = 1120) completed the study: 184 (16%) failed study attention checks meaning 936 were included in the final analysis. Urges to smoke were similar across cue groups. Urges to vape were higher following exposure to vaping compared to neutral cues. There was no clear evidence of an interaction between cue group and smoking or vaping status. The lack of cueing effects on smoking urges is inconsistent with previous research, raising questions about the ability to assess craving in online settings

Impact of health warning labels on selection and consumption of food and alcohol products: systematic review with meta-analysis.

Health warning labels (HWLs) could reduce harmful consumption of food (including non-alcoholic drinks) and alcoholic drinks. A systematic review with meta-analysis using Cochrane methods was conducted to assess the impact on selection (including hypothetical selection) or consumption of food or alcoholic drink products displaying image-and-text (sometimes termed 'pictorial') and text-only HWLs. Fourteen randomised controlled trials were included, three for alcohol, eleven for food. For the primary outcomes, eleven studies measured selection and one measured consumption (two measured only other secondary outcomes). Meta-analysis of twelve comparisons from nine studies (n=12,635) found HWLs reduced selection of the targeted product compared with no HWL (RR=0.74 (95%CI 0.68-0.80)), with participants 26% less likely to choose a product displaying a HWL. A planned subgroup analysis suggested a larger (although not statistically significant) effect on selection of image-and-text HWLs (RR=0.65 (95%CI 0.54-0.80)) than text-only HWLs (RR=0.79 (95%CI 0.74-0.85)). These findings suggest significant potential for HWLs to reduce selection of food and alcoholic drinks, but all experimental studies to date were conducted in laboratory or online settings with outcomes assessed immediately after a single exposure. Studies in field and naturalistic laboratory settings are needed to estimate the potential effects of food and alcohol HWLs.Study registration: PROSPERO 2018 (registration number: CRD42018106522)

Impact of health warning labels on snack selection: An online experimental study.

Excessive consumption of energy-dense food increases the risk of obesity, which in turn increases the risk of non-communicable diseases, including heart disease, type 2 diabetes and most non-smoking-related cancers. Health warning labels (HWLs) that communicate the adverse health consequences of excess energy consumption could reduce intake of energy-dense foods. The aim of the current study was to estimate the impact on selection of energy-dense snacks of (a) image-and-text HWLs (b) text-only HWLs and (c) calorie information. In a between-subjects, 3 (HWL: image-and-text, text-only, no label) x 2 (calorie information: present, absent), factorial experimental design, participants (N = 4134) were randomised to view a selection of energy-dense and non-energy-dense snacks with one of five label types or no label. The primary outcome was the proportion of participants selecting an energy-dense snack in a hypothetical vending machine task. The proportion of participants selecting an energy-dense snack was reduced in all label groups, relative to the no label group (no label: 59%; calories only: 54%; text-only HWL: 48%; text-only HWL with calories: 44%; image-and-text HWL: 37%; image-and-text HWL with calories: 38%). Compared to the no label group, participants were least likely to select an energy-dense snack in the image-and-text HWL group (OR = 0.46, 95%CI = 0.40, 0.54, p < 0.001). Health warning labels - particularly those including an image and text - have the potential to reduce selection of energy-dense snacks in an online setting. Their impact on selection and consumption in real-world settings awaits testing