bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging ChatGPT for systematic reviews: how accurate is it for screening by title and abstract?
Authors: Sciurti A , Migliara G , Isonne C , Siena L M , Marzuillo C , Villari P , Baccolini V 
Published: October 2024

Abstract

Background
Systematic reviews are at the top of the evidence pyramid, but the whole process can be labor-intensive, especially in the screening by title and abstract of retrieved records. Large language models (LLMs), such as ChatGPT, are proficient in natural language processing tasks and offer potential for accelerating this phase. The aim of this study is to assess ChatGPT’s performance in screening records for an already published systematic review (doi: 10.1080/21645515.2023.2300848).

Methods
1601 records with title and abstract were evaluated with ChatGPT 4, using two different prompts to instruct the model: one asking the model to classify each record as included or excluded (Prompt A), and one asking the model to rate each record from 1 to 5 based on inclusion confidence (Prompt B), to compute the model’s performance metrics.

Results
The review included 64 records after title and abstract screening, of which 18 after full text screening. Using records included by title and abstract as a reference, prompt B with a rating cut-off of 3 provided 82% sensitivity, 88% specificity and 99% negative predictive value (NPV). With articles included by full text as a reference, 100% sensitivity, 86% specificity, and 100% NPV. An 85% workload saving was reached. Prompts A showed higher workload savings (∼93%), high NPVs (∼100%) and specificity (∼96%), but lower sensitivity (62-72%).

Conclusions
Prompts with a rating cut-off of 3 achieved a better performance, and still relevant workload savings compared to binary classification prompts. These findings can inform prompt-engineering strategies to instruct LLMs and reach both high sensitivity and workload savings.

Key messages
• Systematic reviews provide evidence synthesis to guide policy and decision-making in healthcare and public health. Such process can be time-consuming, and need for timely evidence is often stringent.
• LLMs can help reduce workload and speed up the title and abstract screening phase of a systematic review, which is considered a major bottleneck in the review process.
Detecting Unrecognized Dementia Using Deep Learning Methods with Korean National Claims Data
Authors: Yoo K B , Nam J W , Lee K M , Kang T H , Yoon J H 
Published: October 2024

Abstract

Background
Dementia is one of the leading causes of death in elderly people. In Korea, the government supports dementia screening for people aged 60 and older, but it is not a population-based organized screening program. It is difficult to achieve early diagnosis and early treatment. The objective of this study is to detect unrecognized dementia using Korean National Claims Data for early diagnosis.

Methods
This study used the National Health Insurance Claims data in Korea. The case group is the new dementia visit as an unrecognized group, while the control group was randomly selected from the general population without dementia. The predictors included health utilization, socioeconomic and demographic, procedure codes, diagnostic codes and health screenings data. The health utilization variables included length of stay, the number of outpatient visits, health expenditures and other encounter information. All medical utilization data was aggregated monthly. In the case group, 12 months of data from 6-month or 2-years before the onset of dementia were used. In the control group, 12 months of data from randomly selected time point were included. Transformer, embedding methods, and Time2Vec were used as the deep learning methods. This study included 453,306 incidents of dementia, representing almost all cases reported from 2010 to 2019 in Korea. The control group consisted of 669,873.

Results
After training the deep learning prediction model, the AUC for 6-month dementia prediction on the test dataset was 0.87, and for 2-year dementia prediction, it was 0.76. The most important variables were health utilization variables, especially health expenditures. The health utilization trajectories of the case group were significantly different from those of the control group.

Conclusions
Based on the claims data, we could detect unrecognized dementia case. We can extend the model to other chronic disease such as cancer and stroke, which are significant burden of disease.

Key messages
• Screening in healthcare facilities or using lab test results would be more accurate, but it would be difficult to apply to a large population due to the cost-effectiveness and timeliness constraints.
• On the other hand, the detection model using the existing claims data would be helpful to to develop cost-effective mass screening program. It can cover the weakness of current screening program.
Preventing type 2 diabetes in Portugal: a novel person-centered digital intervention
Authors: Alves J , Félix I B , Balsa J , Marques M M , Pimenta N , Guerreiro M P 
Published: October 2024

Abstract

Introduction
Diabetes, particularly type 2 diabetes (T2D), stands as one of the leading noncommunicable diseases worldwide. In Portugal, the prevalence of diabetes has surged, with T2D affecting 14% of adults in 2021. Its repercussions extend beyond individual health, deeply impacting familial, social, and community dynamics, presenting a significant public health challenge globally.

Objectives
The VA|PREVENTION project (https://doi.org/10.54499/2022.02969.PTDC) aims to assess the (cost-) effectiveness and implementation of an innovative person-centered digital intervention to prevent T2D among high-risk adults.

Methodology
A comprehensive approach encompasses the Behavior Change Wheel for intervention design, scalability principles, the WHO guidelines for digital health interventions, co-design, and the ISO framework for usability assessment. Evaluation will be pursued through a type 1 hybrid effectiveness-implementation study (randomized controlled trial), supplemented by qualitative and economic studies.

Results
The web application prototype features Ema, an automated virtual human coach (VHC), educational menus and a dashboard (version 1.0). Co-design included 2 workshops with 11 representatives of end-users and health professionals. Ema uses standardized techniques from an ontology to support behavior change, based on an initial assessment of low-level target behaviors (e.g. walking, fruit consumption, and reducing red meat intake), and barriers to performing these behaviors. Ema communicates in a helpful-cooperative style using a synthetic voice in European Portuguese, with its speech also appearing as subtitles on the interface. Users interact with Ema by pressing buttons or entering data, such as the daily number of steps. Ethics approval was granted for usability assessment with end-users.

Conclusions
The project is expected to yield health, scientific, technological, and policy impacts, powered by an exploitation and sustainability roadmap.

Key messages
• Innovative type 2 diabetes prevention through a scalable web app with a virtual human coach.
• Comprehensive and robust approach for developing and evaluating the digital behavior change intervention.
Greenwashing by the fossil fuel industry: impediments to SDGs
Authors: Makhoul J , Talhouk N , Loutfi J , Al-Madhwahi A 
Published: October 2024

Abstract
The fossil fuel industry, a major commercial determinant of public and environmental health, constitutes a central challenge to the achievement of the SDGs. Motivated by profit, the industry has contributed to establishing the current global reliance on fossil fuel as the primary energy source and essential raw material in global production. Major oil companies have purposefully hindered the research and transition towards renewable energy. This was achieved through an intricate web of interference and mechanisms that fall under the corporate playbook, such as political interference through lobbying to stagnate carbon emission reduction, influences on carbon pricing policies, and hinderances to environmental protection legislation. These practices known as ‘greenwashing’ have resulted in misinformation, interfered with climate action in an aim to increase demand for their products, to decrease the pressure from society on the industry, and portray a green image to consumers. Using the commercial determinants of health framework and focusing on the Middle East, this presentation will illustrate how fossil fuel companies falsely advertise their products as environmentally friendly, resulting in environmental degradation, and impede the achievement of most SDGs, especially SDG 3 (good health and wellbeing), SDG 7 (affordable and clean energy), and SDG 13 (climate action).
How Big Tobacco exploits the UN SDGs to advance its own goals
Authors: Nakkash R 
Published: October 2024

Abstract
Globally, the tobacco industry poses a major barrier to the advancement of the Sustainable Development Goals through its influence on SDG 3 (health and well-being), 8 (decent work and economic growth), 13 (climate action), and 17 (partnerships for the goals). Soon after the launch of the SDGs report, Big Tobacco immediately used it to promote its own agenda for development in LMICs such as Lebanon. Using the commercial determinants of health model, this presentation will highlight global and local tobacco monopoly practices, specifically the Lebanese Regie, as a commercial actor and their practices linked to the SDGs to illustrate how the tobacco industry compromises SDG advancement. The presentation will also address some of the system level attributes that serve to perpetuate such practices in Lebanon, allowing for tobacco industry free reign in the country. The presentation will end with suggestions on how LMICs, such as Lebanon, can address the growing industry influence on advances in SDGs and discuss potential measures to curb harmful commercial actor practices.
Digital health divide in Indonesia: evidence from national-level data
Authors: Nababan H 
Published: October 2024

Abstract
Indonesia is a country in south-east Asia with a diverse population and context underlined by its geographical condition as an archipelagic country. Due to closer proximity to the capital, the Western regions (e.g., provinces in Sumatra and Java islands) are relatively more developed than the central and eastern parts of Indonesia (e.g., Nusa Tenggara, Sulawesi, and Papua). In the last few years, the country started to embrace digital transformation for public services including the health sector. Accelerated by the COVID-19 pandemic, a proliferation of digital health services through for example the use of telehealth and health apps is now considered important to improve access and availability of health services, especially among marginalized and hard-to-reach populations. Nonetheless, the difference in access to information and technology infrastructure and services as well as in the level of digital literacy across different regions in Indonesia may perpetuate the existing inequity in access to health services. In 2022, data from the Indonesian Central Bureau of Statistics showed that the level of internet access in Indonesia’s capital Jakarta has reached 85%, while the level in the eastern part of Indonesia (i.e., Papua) is only 26%. Similarly, the level of internet access in the Western provinces tend to be higher than their Eastern counterparts. Additionally, a survey performed by the Ministry of Communication and Informatics to assess the level of digital literacy in Indonesia shows that 85% out of 10,000 respondents accessed the internet through smartphones. However, almost all respondents encounter problems when accessing the internet, especially regarding network quality which causes unstable and frequent connections disconnected. In addition, the level of digital literacy varies across different regions, with the Western region performing better than other regions (e.g., digital literacy index of 3.64 in Yogyakarta vs 3.55 in Papua in 2022).
Radon Exposure Is Associated with Breast Cancer Risk: A Long-Term Population-Based Study from Finland
Authors: Li P , Lin C , Martikainen P , Myrskylä M 
Published: October 2024

Abstract

Background
Radon is a common environmental carcinogen. It is not known whether radon exposure and breast cancer risk are associated at the population level.

Methods
Women continuously living in Finland during the 1987-2016 period were linked to municipality-level indoor radon data annually to estimate their cumulative radon exposure over 30 years. Breast cancer incidence was observed over five years from 2017 onwards. Association between radon exposure and breast cancer incidence was assessed using conditional Cox models adjusted for family history of breast cancer, reproductive history, and socio-demographic covariates. Population attributable fractions (PAF) of breast cancer due to radon exposure were estimated. Robustness analyses were conducted in the population who lived only in houses.

Results
Among 1,335,947 women, 20,067 breast cancer cases were observed during a median follow-up period of 4.9 years. Among women who were exposed to high levels of radon (&gt;100 Bq/m3), overall breast cancer incidence was 10% higher (Hazard ratio 1·10 [95% CI 1·05-1·16]), duct carcinoma incidence was 6% higher (1·06 [1·00-1·13]), lobular carcinoma incidence was 8% higher (1·08 [0·94-1·23]), and the incidence of other morphological sub-types was 34% higher (1·34 [1·17-1·53]) than among other women. Robust associations with overall breast cancer incidence (1·12 [1·05-1·20]) and the incidence of morphological sub-types in the house sample. Correspondingly, suggestive dose-response associations were observed.

Conclusions
High radon exposure is associated with elevated breast cancer risk at the population level, and this relationship is independent of well-established risk factors.

Key messages
• This study investigates the association between long-term radon exposure and breast cancer incidence based on national register data.
• High radon exposure is robustly associated with breast cancer risk in general Finnish population.
Population ageing and health financing: A method for forecasting two sides of the same coin
Authors: Williams G 
Published: October 2024

Abstract
There is a perception that population ageing will have deleterious effects on future health financing sustainability. Given the positive association between health care utilization and increasing calendar age, many analysts assume population ageing will result in considerable growth in health spending. Since this expenditure tends to be sourced primarily from public funds, there is great policy interest to quantify how population ageing is likely to affect health expenditure trends. We propose a new method-the Population Ageing financial Sustainability gap for Health systems (or alternatively, the PASH)-to explore how changes in the population age mix will affect health expenditures and revenues. Using a set of six countries in Europe and the Western Pacific representing a diverse range of health financing systems (Australia, Bulgaria, Japan, Slovenia, United Kingdom, Vietnam), we forecast the size of the ageing-attributable gap between health revenues and expenditures from 2020 to 2100 under current health financing arrangements. The largest gap by 2100 is expected to be in Vietnam, where the gap between revenues and expenditure is expected to increase by around $170 per person in 2018 PPPs or 2.3% of GDP; 87.1% of this increase is due to expected growth in expenditures. In Slovenia, where the gap is forecast in line with the forecast for Japan (the oldest country in the world), nearly half of the gap (44.2%) is due to reductions in revenue generation. All countries face some health financing gap due to ageing under current financing arrangements. The PASH analysis highlights the wide range of policy options available to manage health financing as the population ages, such as changing sources for health revenues and reducing expenditure by promoting healthy ageing.
The value of healthy ageing: Estimating the economic value of health at older ages using time use data
Authors: Santos J V , Cylus J 
Published: October 2024

Abstract
While health naturally has intrinsic value and maintaining health as people age seems to make good economic sense, making the case for investing in health at older ages can be challenging. Much economic growth is historically attributed to the working-age population; however, maintaining good health as people age also enables older people to contribute meaningfully to the economy. Investing in health at older ages, therefore, can be strategic economic policy. We develop a novel method to quantify the economic value of health through time use data. Using data from the United Kingdom Time Use Survey (UKTUS) 2014-15 for individuals aged 65 years-old and older, we apply survey-weighted generalized linear models to predict the time spent in non-market productive activities based on age and self-perceived health. We then quantify the monetary value of time spent engaging in these activities and simulate the monetary impact of health gains at older ages. Both age and self-perceived health status were associated with minutes spent in many non-market productive activities. Being in ‘very good’ instead of ‘very bad’ self-perceived health is associated with an additional production of 439£, 629£, and 598£ per month for an average individual aged 65 to 74 years-old, 75 to 84 years-old, and 85 years-old and older, respectively. Our simulation model indicates that improving the health of 10% of older people in ‘very bad’ health could lead to an economic increase of up to 278£ million through non-market activities. Health at older ages creates considerable economic value which is not captured using standard national accounting measures. Our work highlights the importance of health for functional capacity as people age, allowing them to engage more in non-market activities. Our method to quantify the monetary value of health can be adapted to other settings to make the economic case for investing in healthy ageing.
Ban on mobile phones in the classroom: first (positive) effects
Authors: Boode Karin 
Published: October 2024

Abstract
Karin Boode MBA is Strategic Youth Policy Advisor and working at the National Association of Regional Public Health Services Netherlands. Leading on from the presentation on the harms of social media and smartphones, Karin will present examples of policies that have been successful in reducing the health impacts on youngsters. She will focus on the role of schools in addressing this problem, and how public health organisations can effectively disseminate guidance to teachers and parents in limiting screen time and improving self-regulating behaviours of children and adolescents to minimise screen and smartphone addiction. Karin will also explore controversial legislation such as smartphone bans.
DYNAMO-HIA: A health impact assessment tool fit for quantifying tobacco control policy
Authors: Lhachimi S 
Published: October 2024

Abstract
DYNAMO-HIA is a generic, publicly-available and easy to use software tool for health impact assessments of changes in health risk-factors such as obesity, air pollution, processed meat consumption, physical activity, alcohol taxation, or smoking. The tool uses a graphic use interface, does not require programming skills, and has comparatively modest data requirements. Health outcomes that can be investigated are mortality, life expectancy, healthy-life expectancy, disability and prevalence of various chronic disease such as chronic obstructive pulmonary disease (COPD), cancer, or coronary heart diseases. DYNAMO-HIA can in principle be used for any tobacco control policy or ordinance-e.g. price increases or pictorial health warning labels-that target changes in smoking prevalence or smoking initiation/quitting rates. Past applications of DYNAMO-HIA for tobacco control policy included country studies for Belgium, Mongolia, or Korea and several comparative country studies. In this presentation we will give a general overview into the use of DYNAMO-HIA and show-case a recently published study. This study quantified the reduction in COPD burden that would occur in Italy, England and Sweden over 40 years if tobacco prices were increased by 5%, 10% and 20% over current local prices.
Populating HIA of tobacco policies with empirical evidence on behavioral response to price increases
Authors: De Wit A , Rotteveel A , Lambooij M 
Published: October 2024

Abstract
Performing Health Impact Assessment of tobacco policies requires to have insights into how smokers will react to policy measures such as price increases. In the Netherlands, a series of 3 substantial price increases has been implemented in 2020 (10% increase), 2023 (10% increase) and 2024 (24% increase). We performed three consecutive studies comparing the ex-ante stated preferences about behavioural response to actual and hypothetical future price increases, and compared these stated preferences with actual behaviour changes 6 months after the increase in excise tax. Two of these possible behavioural reactions actually will impact smoking prevalence or smoking intensity, e.g. stopping altogether and decreasing the number of cigarettes smoked. Other behavioural responses are less favourable and will not impact health, such as buying more and cheaper tobacco abroad and smoking less expensive brands or transferring from cigarettes to roll-your-own or e-cigarettes. For the price increases of 2020 and 2023, we have observed a substantial number of about 10% of smokers quitting successfully and about one third attempting to quit smoking. (Attempting to) quit smoking was much more prevalent among those with a more pronounced intention to stop smoking at the ex-ante measurements. At the same time, cross-border shopping increased significantly as well, with a 10 percent-point growth in the absolute amount of all tobacco consumed originating from abroad following the 10 percent price increase of April 2023. This big increase in cross-border shopping appeared to be independent of distance to the border. We conclude that every significant price increase stimulates smokers to consider to stop smoking. However, unilateral price increases in one country will eventually also stimulate smokers to buy cross-border. Behavioural data as presented should inform HIA to make them more realistic with regard to actual behaviour changes and health impacts of smoking policies.