Contains a set of data tables for each part of the Smoking, Drinking and Drug Use among Young People in England, 2021 report

This report contains results from the latest survey of secondary school pupils in England in years 7 to 11 (mostly aged 11 to 15), focusing on smoking, drinking and drug use. It covers a range of topics including prevalence, habits, attitudes, and wellbeing. This survey is usually run every two years, however, due to the impact that the Covid pandemic had on school opening and attendance, it was not possible to run the survey as initially planned in 2020; instead it was delivered in the 2021 school year. In 2021 additional questions were also included relating to the impact of Covid. They covered how pupil's took part in school learning in the last school year (September 2020 to July 2021), and how often pupil's met other people outside of school and home. Results of analysis covering these questions have been presented within parts of the report and associated data tables. It includes this summary report showing key findings, excel tables with more detailed outcomes, technical appendices and a data quality statement. An anonymised record level file of the underlying data on which users can carry out their own analysis will be made available via the UK Data Service later in 2022 (see link below).

Abstract copyright UK Data Service and data collection copyright owner.

The Scottish Health Survey (SHeS) series was established in 1995. Commissioned by the Scottish Government Health Directorates, the series provides regular information on aspects of the public's health and factors related to health which cannot be obtained from other sources. The SHeS series was designed to:

• estimate the prevalence of particular health conditions in Scotland;
• estimate the prevalence of certain risk factors associated with these health conditions and to document the pattern of related health behaviours;
• look at differences between regions and between subgroups of the population in the extent of their having these particular health conditions or risk factors, and to make comparisons with other national statistics for Scotland and England;
• monitor trends in the population's health over time;
• make a major contribution to monitoring progress towards health targets.

Each survey in the series includes a set of core questions and measurements (height and weight and, if applicable, blood pressure, waist circumference, urine and saliva samples), plus modules of questions on specific health conditions that vary from year to year. Each year the core sample has also been augmented by an additional boosted sample for children. Since 2008 NHS Health Boards have also had the opportunity to boost the number of adult interviews carried out in their area.

The Scottish Government Scottish Health Survey webpages contain further information about the series, including latest news and publications.

Scottish Health Survey, 2021: Special Licence Access
The drug and alcohol use questions in the SHeS 2021 young adult and adult self-completions (paper and web) are available under a Special Licence (SL). Most of the variables and derived variables relate to drug use, with a few relating to whether alcohol has been a problem. The rest of the variables relating to alcohol use are available in the Scottish Health Survey, 2021 EUL dataset (available from the UK Data Archive under SN 9048). User are advised to consult the EUL version first before applying for the SL data.

Main Topics:

Illegal drug use and alcohol abuse.

This dataset forms part of the work undertaken for the Wellcome Trust funded project ‘Orphan drugs: High prices, access to medicines and the transformation of biopharmaceutical innovation’ [219875/Z/19/Z]. It comprises of two .csv format files. The data were gathered using the University of Amsterdam Digital Methods Initiative’s ‘Data Tools for YouTube’ tool (DTFY) before being processed and extracted from Gephi (0.9.2) in line with approval form the University of Sheffield School of Sociological Studies Research Ethics Committee (ref: 040659) granted on 14-Jun-2021. The data include a list of 7,469 nodes and 72,9327 edges used within social network analyses of YouTube data around the term 'rare disease'.

Data for A rapid high throughput bioprinted colorectal cancer spheroid platform for in vitro drug- and radiation-response Complete download (zip, 297.8 KiB)

Please note that a slightly amended version of Smoking, drinking and drug use among young people in England: Findings by region, 2006 to 2008, has been made available on this page on 28 January 2010. This was in order to correct the units of Table 5 on page 8 of this report. The units were incorrectly labelled as '%' and have been revised to 'Units of alcohol'. The NHS IC and the National Centre for Social Research (NatCen) apologises for any inconvenience caused. The survey of smoking, drinking and drug use among young people in England (SDD) has been carried out annually by the National Centre for Social Research (NatCen) and the National Foundation for Educational Research (NFER) since 2000. It is commissioned by the NHS Information Centre, with support from the Home Office; the Department for Children, Schools and Families (DCSF) also has an interest in the statistics. This note presents key survey findings by Government Office Region, for secondary school pupils in years 7 to 11 (mostly aged 11 to 15). Results are based on data from the three most recent survey years, 2006 to 2008, combined and weighted to be regionally representative.

Abstract copyright UK Data Service and data collection copyright owner.

The Smoking, Drinking and Drug Use among Young People surveys began in 1982, under the name Smoking among Secondary Schoolchildren. The series initially aimed to provide national estimates of the proportion of secondary schoolchildren aged 11-15 who smoked, and to describe their smoking behaviour. Similar surveys were carried out every two years until 1998 to monitor trends in the prevalence of cigarette smoking. The survey then moved to an annual cycle, and questions on alcohol consumption and drug use were included. The name of the series changed to Smoking, Drinking and Drug Use among Young Teenagers to reflect this widened focus. In 2000, the series title changed, to Smoking, Drinking and Drug Use among Young People. NHS Digital (formerly the Information Centre for Health and Social Care) took over from the Department of Health as sponsors and publishers of the survey series from 2005. From 2014 onwards, the series changed to a biennial one, with no survey taking place in 2015, 2017 or 2019.

In some years, the surveys have been carried out in Scotland and Wales as well as England, to provide separate national estimates for these countries. In 2002, following a review of Scotland's future information needs in relation to drug misuse among schoolchildren, a separate Scottish series, Scottish Schools Adolescent Lifestyle and Substance Use Survey (SALSUS) was established by the Scottish Executive.

The survey uses a two-stage probability sample of schools and pupils, designed to be representative of young people aged between 11 and 15. The sample of schools is stratified by sex of intake and school type. Within these strata, the sampling frame is sorted by local authority. This design does not guarantee a representative sample of schools within all regions and so reliable estimates by region cannot currently be derived from any one year’s data.

This dataset contains regional information as well as key survey variables from the three most recent survey years, 2006 to 2008, combined and weighted to be regionally representative.

Main Topics:

The dataset includes core responses from all pupils who completed a questionnaire in survey years 2006 to 2008. Broad topics included:

• smoking
• drinking
• drug use
• attitudes to smoking, drinking and drug use
• education
• truancy and exclusion
• background information

Could I please request the prescribing data for unlicensed cannabis based medicinal products [CBMP] prescribed privately, from Nov 2018 until the most recent available. I'm particularly looking for the item count, broken down on a monthly basis. Response A copy of the information is attached. Private prescribing of unlicensed cannabis-based medicines November 2018 to March 2023 NHS Prescription Services, within the NHS Business Services Authority (NHSBSA) process prescriptions for Pharmacy Contractors, Appliance Contractors, Dispensing Doctors and Personal Administration. This information is then used to make payments to pharmacists and appliance contractors in England for prescriptions dispensed in primary care settings. There are other arrangements in place for making payments to Dispensing Doctors and Personal Administration. This involves processing over 1 billion prescription items and payments totalling over £9 billion each year. The information gathered from this process is then used to provide information on costs and trends in prescribing in England and Wales to over 25,000 registered NHS and Department of Health and Social Care users. Data Source When prescriptions are processed by the NHSBSA data capture, prescriptions sometimes contain prescribing of medicines that were not populated on the NHSBSA drug database at the time. This type of order will be captured as an ‘unspecified drug.’ Data for prescribing of unlicensed cannabis-based medicines has been taken from data captured as unspecified prescribing. Unlicensed cannabis-based medicines are identified by an additional review process which occurs after the prescriptions have been processed. The items identified by this review are reported against the date that the prescription was written and not necessarily when they were submitted. Therefore, these figures may be subject to change if the prescription is submitted to the NHSBSA in a later month. This dataset This dataset shows total items per month for private prescriptions for unlicensed cannabis-based products. Time Period November 2018 to March 2023 (the latest available month currently). The Data is presented monthly. Organisation Data Data for private unlicensed prescriptions is limited to prescriptions dispensed in England. Items Shows the number of times a product appears on a prescription form not the quantity prescribed.

During discovery and development of protein-based drugs, extensive animal testing is required for preclinical analysis of pharmacokinetics, tissue biodistribution, toxicity, etc. Generally, several animals are required for testing a single drug. We show that the use of genetically encoded peptide barcodes, called flycodes, allows for the simultaneous preclinical assessment of dozens of antibodies from single cassette-dosed mice. Datasets: 1. comparison of flycodes vs. unique endogenous tryptic peptides for antibody identification 2. antibody PK, cassette dose A (high dose) 3. antibody PK, cassette dose B (low dose) 4. antibody tumor/organ biodistribution 5. Dar-SB thermostability 6. Dar-SB PK

Drug treatment for nociceptive musculoskeletal pain (NMP) follows a three-step analgesic ladder, starting from non-steroidal anti-inflammatory drugs (NSAIDs), followed by weak or strong opioids until the pain is under control. Here, we conducted a genome-wide association study (GWAS) of a binary phenotype comparing NSAID users and opioid users as a proxy of treatment response to NSAID using data from the UK Biobank. We aim to find the common genetic variants associated with pain treatment response in the general population.Type of data uploaded in this repositoryUK Biobank is a large-scale biomedical database and research resource containing in-depth genetic and health information from half a million UK participants (https://www.ukbiobank.ac.uk/). The database is globally accessible to approved researchers undertaking vital research into the most common and life-threatening diseases. As the raw data is quite large and only available upon application to UKB, we only provide the results from our analysis, which is also described here: medrxiv and currently in revision in a scientific journal. In the dataset, you will find the association of 9,435,994 SNPs genetic variants with the pain treatment response (PTR) phenotype. This dataset is not applicable to be opened with Excel and can best be opened on a cluster computer or using specific software.SubjectsThe UK Biobank is a general population cohort with over 0.5 million participants aged 40–69 recruited across the United Kingdom (UK). We derived a phenotype as a proxy for the pain treatment response to NSAIDs by using recently released primary care (general practitioners', GPs') data, which contains longitudinal structured diagnosis and prescription data. To define the PTR phenotype, we first extracted all nociceptive musculoskeletal pain (NMP) treatments and diagnoses from the GP data. NMP diagnosis was primarily selected from the chapters on musculoskeletal and connective tissue diseases and relevant symptoms or signs from other chapters in the Read codes (versions 2 and 3). See Supplementary data 1 on medrxiv for the diagnosis codes included in this study. Secondly, pain prescriptions (NSAID and opioid) were extracted from the GP data using the British national formulary (BNF), dictionary of medicines and devices (dmd), and Read code (version 2) for data extraction. An overview of the extracted medication codes is provided in Supplementary data 2 on medrxiv. Only participants with an NMP diagnosis record and a pain prescription record occurring on the same date were included for analysis to ensure that we would only include pain treatment for NMP.PhenotypeBased on the information of NMP and pain prescriptions from the UK biobank, a dichotomous score was used for the binary (case/control) PTR phenotype: NSAID users were defined as controls and opioid users as cases. Two additional quality control (QC) steps were applied. First, participants with only one treatment event were removed to safeguard the inclusion of only participants with relatively long-term treatment. Second, a chronological check was applied for the first prescription of each ladder to ensure that the treatment ladder was correctly followed, i.e., initial NSAID use was followed by weak or strong opioids. Participants that were not treated according to this order were removed.SNP genotyping and quality controlGenotyping procedures have been described in detail elsewhere [PMID: 30305743].The third-release genotyping data were used for analysis (see https://biobank.ctsu.ox.ac.uk/crystal/label.cgi?id=100319).Participants passing quality control were included for analysis. QC steps for the samples included removal of participants with (1) inconsistent self-reported and genetically determined sex, (2) missing individual genetic data with a frequency of more than 0.1, (3) putative sex-chromosome aneuploidy. Participants were also excluded from the analysis if they were considered outliers due to missing heterozygosity, not white British ancestry based on the genotype, and had missing covariate data. Note that when we fit the linear mixed model in GCTA, it reminded us that the number of closely related participants was low. Therefore, we didn't further remove the related individuals in the sample.Routine QC steps for genetic markers on autosomes included removal of single nucleotide polymorphisms (SNPs) with (1) an imputation quality score less than 0.8, (2) a minor allele frequency (MAF) less than 0.005, (3) a Hardy-Weinberg equilibrium (HWE) test P-value less than 1 × 10−6, and (4) a genotyping call rate less than 0.95.Genome-wide association analysisA GWAS for binary PTR phenotype was conducted using a linear function in GCTA [38] for markers on the autosomal chromosomes, adjusting for age, sex, BMI, depression history, smoking status, drinking frequency, assessment center, genotyping array, and the first ten principal components (PCs). The following variables from the UK Biobank data set were...

Compound dataset consisting of structures and bioactivity data (classes) for 512 kinases. Chemical structures are available as InChIKey and bioactivity data as either active (pChEMBL >= 6.5) or inactive (pChEMBL < 6.5) (the meaning of the pChEMBL value can be found on: https://www.ebi.ac.uk/chembl/). The compound structures are chemically standardised by neutralising charges, removing salts, and keeping the largest fragment. The dataset was used in training and validation of statistical models (QSAR and PCM).

IntroductionMost psychiatric inpatients receive psychopharmacological treatment indicated for their mental diseases. The aim of this systematic review is to give clinical pharmacists and physicians a comprehensive summary of common drug-related problems (DRPs) in adult psychiatric inpatients and of potential interventions to solve them in clinical practice.MethodsSix databases and registers were searched for English, German and French articles published between 1999 and 2023 with content regarding the prevalence and/or type or interventions to solve DRPs in adult psychiatric inpatients. Studies were categorized based on types of DRPs and clinical interventions. The prevalence rates of DRPs and subtypes were compared quantitatively and the tested interventions were summarized qualitatively.ResultsA total of 88 articles with an overall sample of over 95.425 adult psychiatric inpatients were included in this review. DRPs were reported with a prevalence range of 0.32 to 9.48 per patient. The most frequently reported DRPs were caused by prescribing errors (1.91 per patient), the most frequent subtype was drug interaction (0.77 per patient). Clinical pharmacists were involved in interventions in 7 of 13 included articles. Interventions consisted of clinical pharmacy services on the ward, educational classes, medication reviews, and the implementation of digital tools such as dispensing cabinets and prescribing tools.DiscussionThe included studies were heterogeneous. The most frequent DRPs in psychiatry are related to prescribing errors and drug interactions. Clinical pharmacists may support the drug therapy by identifying and effectively solving DRPs in psychiatric inpatients using interdisciplinary approaches.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022354958.

Association between metformin and back pain considering age classification.