Pilot trial and process evaluation of a multilevel smoking prevention intervention in further education settings

Background: Preventing smoking uptake among young people is a public health priority. Further education (FE) settings provide access to the majority of 16- to 18-year-olds, but few evaluations of smoking prevention interventions have been reported in this context to date. Objectives: To evaluate the feasibility and acceptability of implementing and trialling a new multilevel smoking prevention intervention in FE settings. Design: Pilot cluster randomised controlled trial and process evaluation. Setting: Six UK FE institutions. Participants: FE students aged 16–18 years. Intervention: ‘The Filter FE’ intervention. Staff working on Action on Smoking and Health Wales’ ‘The Filter’ youth project applied existing staff training, social media and youth work resources in three intervention settings, compared with three control sites with usual practice. The intervention aimed to prevent smoking uptake by restricting the sale of tobacco to under-18s in local shops, implementing tobacco-free campus policies, training FE staff to deliver smoke-free messages, publicising The Filter youth project’s online advice and support services, and providing educational youth work activities. Main outcome measures: (1) The primary outcome assessed was the feasibility and acceptability of delivering and trialling the intervention. (2) Qualitative process data were analysed to explore student, staff and intervention team experiences of implementing and trialling the intervention. (3) Primary, secondary and intermediate (process) outcomes and economic evaluation methods were piloted. Data sources: New students at participating FE settings were surveyed in September 2014 and followed up in September 2015. Qualitative process data were collected via interviews with FE college managers (n = 5) and the intervention team (n = 6); focus groups with students (n = 11) and staff (n = 5); and observations of intervention settings. Other data sources were semistructured observations of intervention delivery, intervention team records, ‘mystery shopper’ audits of local shops and college policy documents. Results: The intervention was not delivered as planned at any of the three intervention settings, with no implementation of some community- and college-level components, and low fidelity of the social media component across sites. Staff training reached 28 staff and youth work activities were attended by 190 students across the three sites (< 10% of all eligible staff and students), with low levels of acceptability reported. Implementation was limited by various factors, such as uncertainty about the value of smoking prevention activities in FE colleges, intervention management weaknesses and high turnover of intervention staff. It was feasible to recruit, randomise and retain FE settings. Prevalence of weekly smoking at baseline was 20.6% and was 17.2% at follow-up, with low levels of missing data for all pilot outcomes. Limitations: Only 17% of eligible students participated in baseline and follow-up surveys; the representativeness of student and staff focus groups is uncertain. Conclusions: In this study, FE settings were not a supportive environment for smoking prevention activities because of their non-interventionist institutional cultures promoting personal responsibility. Weaknesses in intervention management and staff turnover also limited implementation. Managers accept randomisation but methodological work is required to improve student recruitment and retention rates if trials are to be conducted in FE settings. Trial registration: Current Controlled Trials ISRCTN19563136. Funding: This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 5, No. 8. See the NIHR Journals Library website for further project information. It was also funded by the Big Lottery Fund

The Grizzly, February 26, 2015

We\u27re Just Saying Ursinus Discusses Diversity on Campus • Alumni Invited to Classes • Composting Initiative in Lower Fails to Take Hold • Stereotypes in U.S. Colleges • Math Department Struggles • Satirical Blog Gains Campus Popularity • Professor Releases Poetry Book • New Officer Joins Safety • Opinion: The Gray Area in Fifty Shades; Ursinus Has a Responsibility to Ban Yik Yak • Wrestling Prepares for Regional Meet • Bears Two Much to Handlehttps://digitalcommons.ursinus.edu/grizzlynews/1925/thumbnail.jp

Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery

Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our objective was to determine whether two LLMs can serve information needs submitted by physicians as questions to an informatics consultation service in a safe and concordant manner. Sixty six questions from an informatics consult service were submitted to GPT-3.5 and GPT-4 via simple prompts. 12 physicians assessed the LLM responses' possibility of patient harm and concordance with existing reports from an informatics consultation service. Physician assessments were summarized based on majority vote. For no questions did a majority of physicians deem either LLM response as harmful. For GPT-3.5, responses to 8 questions were concordant with the informatics consult report, 20 discordant, and 9 were unable to be assessed. There were 29 responses with no majority on "Agree", "Disagree", and "Unable to assess". For GPT-4, responses to 13 questions were concordant, 15 discordant, and 3 were unable to be assessed. There were 35 responses with no majority. Responses from both LLMs were largely devoid of overt harm, but less than 20% of the responses agreed with an answer from an informatics consultation service, responses contained hallucinated references, and physicians were divided on what constitutes harm. These results suggest that while general purpose LLMs are able to provide safe and credible responses, they often do not meet the specific information need of a given question. A definitive evaluation of the usefulness of LLMs in healthcare settings will likely require additional research on prompt engineering, calibration, and custom-tailoring of general purpose models.Comment: 27 pages including supplemental informatio

Pilot trial and process evaluation of a multi-level smoking prevention intervention in further education settings

Background: Preventing smoking uptake among young people is a public health priority. Further education (FE) settings provide access to the majority of 16- to 18-year-olds, but few evaluations of smoking prevention interventions have been reported in this context to date. Objectives: To evaluate the feasibility and acceptability of implementing and trialling a new multilevel smoking prevention intervention in FE settings. Design: Pilot cluster randomised controlled trial and process evaluation. Setting: Six UK FE institutions. Participants: FE students aged 16–18 years. Intervention: ‘The Filter FE’ intervention. Staff working on Action on Smoking and Health Wales’ ‘The Filter’ youth project applied existing staff training, social media and youth work resources in three intervention settings, compared with three control sites with usual practice. The intervention aimed to prevent smoking uptake by restricting the sale of tobacco to under-18s in local shops, implementing tobacco-free campus policies, training FE staff to deliver smoke-free messages, publicising The Filter youth project’s online advice and support services, and providing educational youth work activities. Main outcome measures: (1) The primary outcome assessed was the feasibility and acceptability of delivering and trialling the intervention. (2) Qualitative process data were analysed to explore student, staff and intervention team experiences of implementing and trialling the intervention. (3) Primary, secondary and intermediate (process) outcomes and economic evaluation methods were piloted. Data sources: New students at participating FE settings were surveyed in September 2014 and followed up in September 2015. Qualitative process data were collected via interviews with FE college managers (n = 5) and the intervention team (n = 6); focus groups with students (n = 11) and staff (n = 5); and observations of intervention settings. Other data sources were semistructured observations of intervention delivery, intervention team records, ‘mystery shopper’ audits of local shops and college policy documents. Results: The intervention was not delivered as planned at any of the three intervention settings, with no implementation of some community- and college-level components, and low fidelity of the social media component across sites. Staff training reached 28 staff and youth work activities were attended by 190 students across the three sites (< 10% of all eligible staff and students), with low levels of acceptability reported. Implementation was limited by various factors, such as uncertainty about the value of smoking prevention activities in FE colleges, intervention management weaknesses and high turnover of intervention staff. It was feasible to recruit, randomise and retain FE settings. Prevalence of weekly smoking at baseline was 20.6% and was 17.2% at follow-up, with low levels of missing data for all pilot outcomes

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe