The adaptation of noise-induced temporary hearing threshold shift predictive models for modelling the public health policy.

OBJECTIVES: It has been shown that monitoring temporary threshold shift (TTS) after exposure to noise may have a predictive value for susceptibility of developing permanent noise-induced hearing loss. The aim of this study is to present the assumptions of the TTS predictive model after its verification in normal hearing subjects along with demonstrating the usage of this model for the purposes of public health policy. MATERIAL AND METHODS: The existing computational predictive TTS models were adapted and validated in a group of 18 bartenders exposed to noise at the workplace. The performance of adapted TTS predictive model was assessed by receiver operating characteristic (ROC) analysis. The demonstration example of the usage of this model for estimating the risk of TTS in general unscreened population after exposure to loud music in discotheque bars or music clubs is provided. RESULTS: The adapted TTS predictive model shows a satisfactory agreement in distributions of actual and predicted TTS values and good correlations between these values in examined bartenders measured at 4 kHz, and as a mean at speech frequencies (0.5-4 kHz). An optimal cut-off level for recognizing the TTS events, ca. 75% of young people (aged ca. 35 years) may experience TTS >5 dB, while <10% may exhibit TTS of 15-18 dB. CONCLUSIONS: The final TTS predictive model proposed in this study needs to be validated in larger groups of subjects exposed to noise. Actual prediction of TTS episodes in general populations may become a helpful tool in creating the hearing protection public health policy. Int J Occup Med Environ Health. 2023;36(1):125-38.

Resting-state Networks in Tinnitus : A Scoping Review.

Chronic subjective tinnitus is the constant perception of a sound that has no physical source. Brain imaging studies show alterations in tinnitus patients' resting-state networks (RSNs). This scoping review aims to provide an overview of resting-state fMRI studies in tinnitus, and to evaluate the evidence for changes in different RSNs. A total of 29 studies were included, 26 of which found alterations in networks such as the auditory network, default mode network, attention networks, and visual network; however, there is a lack of reproducibility in the field which can be attributed to the use of different regions of interest and analytical methods per study, and tinnitus heterogeneity. Future studies should focus on replication by using the same regions of interest in their analysis of resting-state data, and by controlling adequately for potential confounds. These efforts could potentially lead to the identification of a biomarker for tinnitus in the future.

The Need for Data Contextualization in Urban-Water Systems in Terms of Environmental and Behavioural Health.

The current paper addresses the need for making scientific knowledge easily accessible, comprehensible, and tailored for citizens, especially in urban-water habitats, enabling their behavioural change and consequent climate change resilience. It proposes a schema that integrates data from different sources and highlights their relevance to citizens (aiming to raise their awareness), the impact on the citizens' Quality of Life as well as the way they (will have to) perform various activities. Targeted bibliographical research through online digital libraries was conducted to capture the scientific coverage and validation of this need. As an outcome, the complexity and interdependencies of environmental and behavioural health issues growth has been confirmed, and public health programs have begun to identify the need for the integration of data from diverse sources. Therefore, the proposed schema could be used for enabling better design of public health policy making.

Public health policy-making for hearing loss: stakeholders' evaluation of a novel eHealth tool.

BACKGROUND: Hearing loss (HL) affects 466 million people of all ages worldwide, with a rapidly increasing prevalence, and therefore requires appropriate public health policies. Multi-disciplinary approaches that make use of eHealth services can build the evidence to influence public policy. The European Union-funded project EVOTION developed a platform that is fed with real-time data from hearing aids, a smartphone, and additional clinical data and makes public health policy recommendations based on hypothetical public health policy-making models, a big data engine and decision support system. The present study aimed to evaluate this platform as a new tool to support policy-making for HL. METHODS: A total of 23 key stakeholders in the United Kingdom, Croatia, Bulgaria and Poland evaluated the platform according to the Strengths, Weaknesses, Opportunities and Threats methodology. RESULTS: There was consensus that the platform, with its advanced technology as well as the amount and variety of data that it can collect, has huge potential to inform commissioning decisions, public health regulations and affect healthcare as a whole. To achieve this, several limitations and external risks need to be addressed and mitigated. Differences between countries highlighted that the EVOTION tool should be used and managed according to local constraints to maximise success. CONCLUSION: Overall, the EVOTION platform can equip HL policy-makers with a novel data-driven tool that can support public health policy-making for HL in the future.

Applying a general systems theory framework in mental health treatment pathways: the case of the Hellenic Center of Mental Health and Research.

Language, socio-emotional and cognitive development in children and adolescents with mental health issues is getting increased attention over the last years. Establishing communication patterns and addressing behavioural diversities among this population should be of priority, along with a better understanding in a large variety of patient characteristics within the operational framework of mental healthcare centers. Therefore, the relationships between provided services and operational capability should become more evident. As integrated systems' approaches are still missing to predict the efficiency of treatment services in a macroscopic scale, a General Systems Theory framework is hereby proposed. This framework is applied and tested against the operational framework of the Hellenic Center of Mental Health and Research, in order to identify the need of such an approach and the strong cooperation between medical and population interactions. Using such frameworks as a prerequisite to identify important factors affecting population states can lead to evaluating their impact on the treatment outcome and depict the complexity of pathways potentially related to the children's development.

Challenges and Strengths of Multidisciplinary Research in Audiology: The EVOTION Example.

Purpose The EU-funded research project EVOTION has brought together clinical, technical, and public health experts with the aim to offer a solution for the holistic management of hearing loss. This report presents the challenges, strengths, and key take-home messages of working in this multidisciplinary consortium. Method Fifteen consortium members completed an online survey with 6 open-ended questions. Responses were analyzed using a thematic approach. Results Analysis identified 4 main themes: (a) communication, that is, cross-disciplinary communication difficulties but also range of expertise; (b) opportunities, that is, innovation, learning, and collaborations; (c) technology, that is, technical requirements and data collection and management issues; and (d) local constraints, that is, institutional limitations, resources, and planning. Conclusions Although the challenges reported differed by country and specialty, there was consensus about the value, expertise, and opportunities of the project. It is recommended that in future similar multidisciplinary projects in audiology, researchers establish a common language and assess technical requirements and local constraints prior to initiating research activities.

Evaluation for the Necessity of Medical Imaging Tests Prescription in Neurology.

The evaluation and control algorithms for the necessity of medical prescription testing, comprises useful tool for health professionals. It is beyond doubt that a connection between illness, symptoms, medical tests and prescriptions is essential and thus algorithms facilitating such approaches should be available to health professionals. Such informatics tools require the implementation of smart, interactive tools and not just linear, information storing websites. Such algorithms should be dynamic, that is their output should change based on the input as for example, in the serial input of symptoms to clinical examination to subsequent diagnosis. Slight variations in symptomatology can greatly alter diagnosis and subsequent physical testing and prescription. The present work presents a novel algorithm for the control of medical prescription testing in neurology, by utilizing decision trees for the connection of symptomatology to diagnosis and prescription for neurological conditions and disease. To the best of our knowledge this is the first time that such an approach is proposed.

Big Data for Sound Policies: Toward Evidence-Informed Hearing Health Policies.

PURPOSE: The scarcity of health care resources calls for their rational allocation, including within hearing health care. Policies define the course of action to reach specific goals such as optimal hearing health. The process of policy making can be divided into 4 steps: (a) problem identification and issue recognition, (b) policy formulation, (c) policy implementation, and (d) policy evaluation. Data and evidence, especially Big Data, can inform each of the steps of this process. Big Data can inform the macrolevel (policies that determine the general goals and actions), mesolevel (specific services and guidelines in organizations), and microlevel (clinical care) of hearing health care services. The research project EVOTION applies Big Data collection and analysis to form an evidence base for future hearing health care policies. METHOD: The EVOTION research project collects heterogeneous data both from retrospective and prospective cohorts (clinical validation) of people with hearing impairment. Retrospective data from clinical repositories in the United Kingdom and Denmark will be combined. As part of a clinical validation, over 1,000 people with hearing impairment will receive smart EVOTION hearing aids and a mobile phone application from clinics located in the United Kingdom and Greece. These clients will also complete a battery of assessments, and a subsample will also receive a smartwatch including biosensors. Big Data analytics will identify associations between client characteristics, context, and hearing aid outcomes. RESULTS: The evidence EVOTION will generate is relevant especially for the first 2 steps of the policy-making process, namely, problem identification and issue recognition, as well as policy formulation. EVOTION will inform microlevel, mesolevel, and macrolevel of hearing health care services through evidence-informed policies, clinical guidelines, and clinical care. CONCLUSION: In the future, Big Data can inform all steps of the hearing health policy-making process and all levels of hearing health care services.

The EVOTION Decision Support System: Utilizing It for Public Health Policy-Making in Hearing Loss.

As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data. Expected outcomes for this joint effort are discussed from a public-health point of view.

Associations Between Hearing Performance and Physiological Measures - An Overview and Outlook.

The current paper summarises the research investigating associations between physiological data and hearing performance. An overview of state-of-the-art research and literature is given as well as promising directions for associations between physiological data and data regarding hearing loss and hearing performance. The physiological parameters included in this paper are: electrodermal activity, heart rate variability, blood pressure, blood oxygenation and respiratory rate. Furthermore, the environmental and behavioural measurements of physical activity and body mass index, alcohol consumption and smoking have been included. So far, only electrodermal activity and heart rate variability are physiological signals simultaneously associated with hearing loss or hearing performance. Initial findings suggest blood pressure and respiratory rate to be the most promising physiological measures that relate to hearing loss and hearing performance.