bluuebunny/crossref_metadata_2025_split huggingface dataset:
Defining child maltreatment for research and surveillance: a Delphi study in 34 countries
Authors: Hurt L , Cowley L E , Lamela D , Drabarek K , Rodrigues L B , Laajasalo T , Naughton A , Ntinapogias A , Nurmatov U 
Published: October 2024

Abstract

Background
Child maltreatment is a complex public health issue that has consequences across the life-course. Studies to measure child maltreatment and identify interventions and services are constrained by a lack of uniform definitions across sectors and countries. We conducted a Delphi study to reach consensus on types and characteristics of child maltreatment for use in surveillance and research in Europe.

Methods
Statements were developed following a scoping review and identification of key concepts by an international expert team (n = 19). A multidisciplinary expert panel (n = 70) from 34 countries participated in three rounds of online data collection. We defined consensus as ≥ 70% agreement or disagreement with each statement after the final round.

Results
Consensus was reached on 26/31 statements, with a participant retention rate of 94%. The definition states that child maltreatment is a subtype of violence against children. The perpetrator can be an adult or minor, but must be in a position of power over the child. To define an act or omission as child maltreatment, it must cause harm or have the potential to cause harm, regardless of intention, severity, chronicity, or the traditional/cultural beliefs of the perpetrator. In addition, the broad umbrella term encompassing emotional, behavioural or cognitive maltreatment should be “psychological”, and psychological maltreatment should be split into sub-types of psychological abuse and psychological neglect. “Neglect” is a broad type of child maltreatment within which there are subtypes that can all be characterised as “failure to provide” or “failure to supervise”.

Conclusions
This is the first study to demonstrate consensus on the types and key characteristics of child maltreatment across multiple sectors and countries, providing a unified definition of child maltreatment to improve consistency of measurement and surveillance in Europe. This abstract is submitted on behalf of Working Group 1 COST Action 19106.

Key messages
• A standardised definition is essential for monitoring child maltreatment.
• We propose a consensus-based definition that can be used to improve child maltreatment measurement in research and surveillance.
“The Church of Fail”: Learning from Our Mistakes in Co-Creation (part II)
Authors: Ryom K , Agnello D , Jacobsen J S , Laursen M G , McCaffrey L , Vogelsang M , Chastin S 
Published: October 2024

Abstract

For the second activity, participants will be invited to break into smaller facilitated groups for a ‘peer-to-peer’ session where they will share further and discuss lessons learned and how they would do things differently going forward. They will do this by either working with one of their own failure stories/cases, or a predetermined case around critical aspects of co-creation, such as power imbalance or recruitment strategies. The groups will work with a facilitator and a template to discuss some key aspects of learning, such as what do you perceive as the failure, how could you address this, and the changes they could be made moving forward. The second session closes with each group nominating a presenter to share their reflections on the proposed solutions in plenary. The facilitator will close the workshop by inviting participants to sign up to join a collaborative effort to publish examples of failures and lessons learned when addressing complex public health challenges. This has the potential to increase awareness about the importance of embracing the power of failure, and break down the stigma that comes with admitting to your mistakes.

Speakers/Panelists
Sebastien Chastin
Glasgow Caledonian University, Glasgow, UK
Integrating AI in cause-of-death regular statistical production with human and expert system codings
Authors: Zambetta E , Razakamanana N , Robert A , Martin D , Coudin E 
Published: October 2024

Abstract

Background
Cause-of-death (CoD) statistics are key indicators in epidemiology and public health. These statistics are derived from death certificates completed by physicians and are usually coded by official statistics authorities according to the standards of the WHO ICD-10 classification to construct time- and cross-country-comparable statistics. For coding causes of death in free-text format in France according to ICD-10, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team.

Methods
Seq-to-seq DNNs are trained from scratch on previously coded data to ICD-10 code multiple causes and underlying causes of death. Human coding is focused on certificates with a special public health interest or with low confidence in AI prediction quality to maximize the quality of the overall statistics disseminated when human resources are limited. DNNs also directly predict multiple causes and underlying causes of death for part of the certificates. Hence, the coding campaign aims to optimally allocate a coding mode to a given certificate.

Results
For deaths in 2021, 63% of the certificates are automatically batch coded by the expert system, 14% by the coding team, and 23% by DNNs. Compared to a traditional campaign that would have relied on automatic batch coding and manual coding, the present campaign reaches an accuracy of 95.7% for ICD-10 coding of the underlying cause (97.3% at the European shortlist level).

Conclusions
The 3-coding mode approach enables timeliness of dissemination of CoD statistics and may lead in the future to more responsive surveillance.

Key messages
• Deep neural networks trained on already coded data can be integrated into the regular statistical production of the CoD database in a fully controlled way.
• The allocation between the different modes of coding can be optimized to achieve best quality and timeliness under the constraint of limited human resources.
Effects of metaphorical communication on vaccine confidence in the adolescent population
Authors: Nuccetelli F , Gabellone V , Gabrielli E , Lopalco P L 
Published: October 2024

Abstract

Vaccine hesitancy, defined as delay or refusal of vaccination despite the availability of vaccination services, has been included by WHO among the top 10 global health threats. Individual decision-making process can be strongly affected by communication. The use of metaphors is common in public health communication and increased during the COVID19 pandemic. Although some evidence has supported the persuasive potential of metaphorical language over scientific language, further research is needed. Our study aimed at comparing the effects of neutral scientific talk with war and protective metaphors on health communication. An online survey was conducted on a convenience sample of Italian teenagers randomly allocated to three study arms. Each participant was invited to watch a specific version of an informative video on infections and vaccines (group 1: neutral-scientific approach, group 2: metaphorical-war, and group 3: metaphorical-protective approach). After watching the video, each participant responded to an ad-hoc questionnaire. A total of 2681 subjects were randomly allocated to the three groups. No significant differences regarding age, sex and geographical area were detected between groups. Median age of the sample was 17 years (mean 16,8) and 56.8% were girls. The general attitude towards vaccination in group 2 and 3 was largely positive, with the majority agreeing (strongly or tend to agree) on the fact that vaccination is important (group 2: 89%; group 3: 92%), safe (group 2: 91%; group 3: 92,5%), effective (group 2: 85%; group 3: 88%), and does not generate anxiety (group 2: 80%; group 3: 83%). Higher level of distrust against vaccines was found in group 1, where 32% of participating adolescents are strongly or tend to be anxious about getting vaccinated. The results of our survey suggest that emotional involvement evoked through the use of metaphorical language may have, at least in the short run, some positive effect on vaccine confidence.

Key messages
• Use of metaphors can be successfully used in public health communication.
• Messages evoking either war or protecting concepts are more efficacious than plain scientific language.
Artificial intelligence – NPHIs’ role in utilizing its opportunities and addressing the risks
Authors: Habl C , Ottersen T 
Published: October 2024

Abstract

Issue & Problem
National Public Health Institutes (NPHIs) in many countries are at the forefront of action to mitigate the impact of current and future threats to health as well as improving population health and wellbeing. Through research, collaboration, and support, NPHIs can approach these new realities together. One of the many emerging realities that NPHIs will need to engage in is how NPHIs best can utilise the powers of artificial intelligence and deal with the ethical and legal issues that come with it.

Methods
In preparation of IANPHI’s (International Association of National Public Health Institutes) Europe Regional network meeting in April 2024 a survey was conducted among the 42 members. 16 countries replied to questions, around e.g., 1) current applications of (generative) artificial intelligence (AI) in the work of institutes, 2) which experiences were made and 3) which measures NPHIs take to best utilize the possibilities and overcome challenges of AI technologies. Within four weeks 16 replies were shared.

Lessons & Conclusions
Some institutes have not yet adopted AI, while others report multiple applications but the primary areas of application vary considerably among Europe.

Applications include
summarizing and reformatting text; translation; transcribing and documenting meetings; search information in documents or databases; coding; creating visuals; literature review; surveillance of infectious diseases; disease forecasting; analysis of transmission dynamics; vaccine efficacy assessment and development; image recognition; diagnosis and prediction of diseases from medical datasets; text mining; symptom extraction; social listening; prediction of nitrate concentration in groundwater; drug analysis and measuring psychological resilience in social crisis.

Key messages
• AI poses opportunities and risks for public health and work of national public health institutes and capacity building initiatives are essential.
• IANPHI decided to develop a joint framework for the use of AI in its member organisations with a focus on research and responsible use.
Luton, a Marmot town – using a whole-system approach to tackle health equity
Authors: Cartwright S , Egbutah C , Allen J , Ravindrane R , Austin-Croft L , Ali N 
Published: October 2024

Abstract

Issue
Luton has high deprivation and health inequalities. We have a borough-wide vision that no one should live in poverty by 2040, and have become a health equity town - committed to Marmot policy objectives and recommendations across all we do.

Description
Luton is 70th most deprived local authority in England, with stark health inequalities. To deliver the 2040 ambition, 5 pillars have been established, including tackling health inequalities. Luton has become the first Marmot Town in the UK, working with the Institute of Health Equity to develop recommendations and actions relating to the Marmot Policy objectives. Cross-sector system partnership has been key -NHS, businesses, housing, voluntary sector, university. Year 1: we mapped the Marmot recommendations to existing workstreams; completed a mixed-methods evaluation to understand system views of the approach and establish our impact measures. We established steering groups: Children and young people; Housing; Employment and skills; Net zero, they continue to embed recommendations using logic models. We have an overarching strategic approach, alongside smaller scale programmes, to create a movement. Including: grant funding; regular newsletter; training; case studies repository and annual celebration event.

Results
We have established 15 impact measures across Marmot policy areas to review annually. Qualitative evaluation findings built into work plans include: improved governance and accountability; workforce development across the system; use of logic models; Learning from best practice; sharing knowledge and learning.

Lessons
The wider agenda of Luton 2040 has enabled health inequalities to be embedded into strategic discussions; improved evidence base and clear narrative to support priorities is helpful; clear focused recommendations helps move work forwards; shared understanding of how we will measure long term impact is vital, communicating to the system is key, and long-term ism challenging.

Speakers/Panelists
Lee Watson
East of England Public Health Training Programme, Luton, UK
Ramya Ravindrane
East of England Public Health Training Programme, Luton, UK
Chimeme Egbutah
Luton Borough Council, Luton, UK
Nasreen Ali
University of Bedfordshire, Luton, UK
Estimated lifetime impact of a school-based intervention for mental health: A microsimulation study
Authors: Bates S , Saidi Y , Cookson R , Skarda I , Ford T , Hayes R , Ganguli P , Byford S , Brennan A 
Published: October 2024

Abstract

Background
The prevalence of childhood mental health problems is increasing. School-based interventions have the potential to reduce poor mental health and mental health inequalities. Our aim was to estimate the long-term costs and benefits of the Incredible Years Teacher® Classroom Management (IY-TCM) intervention in primary schools compared to no intervention.

Methods
LifeSim, an existing microsimulation model, was used to estimate the lifetime costs and benefits of IY-TCM by linking short-term changes in SDQ based on a previous trial in primary schools (Cluster RCT: 2075 children aged 4-9 years with a 30-month follow-up) to long-term health, social, economic and wellbeing outcomes. Benefits were measured in quality adjusted life years and wellbeing adjusted life years. We examined subgroup based on deprivation, conduct scores and parental depression.

Results
Microsimulation modelling estimated small gains in lifetime outcomes including reduced conduct disorder in adolescence and depression in adulthood. Estimates indicate IY-TCM could be cost-effective with a large amount of uncertainty (Net monetary benefit (NMB)=£21, Estimated CI = -£195, £240). IY-TCM was estimated to be more cost-effective for those with high deprivation (NMB = £231, Estimation CI - -£99, £231) and high conduct problem scores (NMB=£315, Estimated CI = £45, £483). Total net social benefit for a typical year size group was estimated to be £111m.

Conclusions
IY-TCM could be cost-effective compared to no intervention with a large estimated social benefit supporting wider implementation of IY-TCM, but results indicate a large amount of uncertainty. Greater benefits and higher certainty of cost-effectiveness for children with conduct problems and those living in a deprived area suggest IY-TCM has the potential to reduce mental health inequalities and may be more cost-effective for schools with higher deprivation and/or a high prevalence of conduct problems.

Key messages
• The Incredible Years Teacher Classroom Management intervention for mental health in primary schools could be considered cost-effective but there is a large amount of uncertainty.
• Greater benefits for children with conduct problems and those living in a deprived area indicates the intervention has the potential to reduce mental health inequalities.
Exploring support for return-to-work: A comparative analysis of firm and country-level factors
Authors: Leoni T 
Published: October 2024

Abstract

Background
Employers are important stakeholders in efforts to facilitate the return-to-work (RTW) of employees after sick-leave, but the available data reveal large variation in employer support for RTW across European countries and firms. This paper explores in a comparative perspective what factors at the country level and at the firm level can explain these differences.

Methods
Employer support for RTW is examined using microdata covering 31 countries from the Third European Survey of Enterprises on New and Emerging Risks (ESENER), conducted in 2019 (N = 9,775). These data are integrated with country-level indicators to capture national differences in economic incentives and institutional provisions concerning the management of sick-leave. Two-level mixed-effects logit models with random intercepts are used to estimate the impact that different firm characteristics and country-level factors have on the propensity to provide RTW support.

Results
The empty model has an intraclass correlation coefficient (ICC) of 0.345, indicating that a substantial share of the observed variation across European firms is determined at the country level. Larger establishments and those with workplace health risks are more likely to provide RTW support. Including firm-level indicators does however not reduce the observed between-country variance. Institutional differences in the economic costs of sick leave for employers, on the other hand, explain about 15% of this variance. The ICC drops more strongly after including in the model policy indicators that capture activating elements in the social security system and the existence of national policies targeting RTW. The full model explains almost two thirds (62.8%) of the observed between-country variance.

Conclusions
The findings highlight that only in few European countries employers are systematically involved in RTW support and strengthen the case for comprehensive policy strategies to engage employers in worker activation.

Key messages
• Employer characteristics, such as firm size, impact the propensity to provide RTW support, but they do not explain the large between-country variation that we observe across Europe.
• Comprehensive national policy strategies and institutional incentives are crucial to engage employers systematically in RTW efforts.
Cost-effectiveness analysis of screening three-year old for social-emotional problems
Authors: Manzano A , Pulkki-Brännström A-M , Ivarsson A , Vaezghasemi M , Feldman I 
Published: October 2024

Abstract

Aim
To assesses the long-term cost-effectiveness of a population-based screening to detect social-emotional problems at 3-years-old combined with an evidence-based intervention to prevent mental health problems.

Methods
A decision-analytic Markov model compares two alternatives 1) all 3-years-old get screened for social-emotional problems, and parents for children at a high risk receive a generic targeting parenting intervention 2) no screening and no intervention. The cohort of 3-year-old is modeled until they are 19 years old. The screening test is the ASQ:SE and the intervention was given to children with scores that suggest social-emotional problems. The model considered development of anxiety, conduct problems, and ADHD, over the 16 years. The analyses were done from a societal and healthcare perspectives. Health outcomes were assessed with DALYs averted.

Results
Results suggest that the probability of population-based screening for social-emotional problems combined with the parenting intervention to high risk-children being cost-effective is high, adopting a societal and healthcare perspective, 98% and 97% each. From a societal perspective, the likelihood of cost saving is high, 85 %. The combination of screening and intervention strongly dominated the comparator.

Conclusions
The findings align with previous research; prevention aimed at children’s mental health disorders will likely yield high investment returns. Successful implementation of population-based screening for social-emotional problems combined with an effective evidence-based parenting intervention might be an important way to contribute to sustainable and efficient mental health care.

Key messages
• The impact of combining population-based screening with intervention is encouraging when considering a long-term view.
• Prevention aimed at children’s mental health will likely yield high investment return.
The corporate political activity of Portugal’s food industry: enhancing public health transparency
Authors: da Costa S , Mialon M , Graça P , Gregório M J 
Published: October 2024

Abstract

Background
This study in Portugal aims to monitor the Corporate Political Activity (CPA) in the food industry. Portugal provides a compelling case study due to its robust implementation of public health policies.

Methods
A systematic qualitative approach proposed by Mialon et al., a part of the INFORMAS Module 3, was employed. This method is based on the analysis of publicly available information. Key industry actors were selected through expert consultation and market analysis using EuroMonitor data. Information sources included industry, government, and academic materials accessed via websites and news. A thematic qualitative analysis was conducted involving iterative steps: identifying CPA practices based on predefined strategies - Taxonomy of Action Strategies: access and influence policymaking, use the law to obstruct policies, manufacture public support, shape evidence, displace and usurp public health, and manage reputations -, recording methods in a database, and saving evidence. Data collection spanned October 2023 to April 2024, covering materials from 2022 to 2023.

Results
Twenty-five key players were identified, including processed food and non-alcoholic beverage manufacturers, fast food companies, food retailers, and national trade associations. Food retailers, notably Jerónimo Martins, Lidl, Mercadona, and Sonae, showcased a higher prevalence of CPA. Nestlé and Sumol+Compal also emerged as prominent actors. The food industry in Portugal employs diverse strategies and tactics primarily focused on shaping evidence and managing reputations. While instances of displacing public health priorities and manufacturing public support were observed, they were relatively fewer. Only APED and FIPA showed engagement in policymaking influence.

Conclusions
Vigilant monitoring of CPA in the food industry in Portugal reveals dominant tactics of shaping evidence and managing reputations. Understanding these strategies is vital for policymaking to safeguard public health.

Key messages
• The food industry in Portugal employs diverse strategies, primarily shaping evidence and managing reputations, to influence public health policies.
• Monitoring the Corporate Political Activity is key to preserving the integrity of public health policymaking in Portugal’s food industry.