OBJECTIVE: To explore the amount and type of research funded under relevant Medical Research Future Fund (MRFF) Initiatives that addressed public health and prevention from 2018 to July 2023.
METHODS: Projects funded by six MRFF Initiatives, with objectives relevant to public health and public health nominated as \"field of research\" by >25% of applicants, were evaluated against a set of public health research criteria and were categorised based on levels of prevention.
RESULTS: Fifty-seven per cent of 249 funded projects were categorised as public health research. Projects with curative features, focusing on tertiary (32%) and quaternary (4%) prevention, were as common as projects with earlier preventive features, focussed on primordial (7%) and primary (28%) prevention. The Preventive and Public Health Research Initiative had the lowest proportion of public health research (48%) of the six evaluated Initiatives and a dominance of curative (39%) and non-preventive (26%) research over preventive research (30%).
CONCLUSIONS: This study highlighted variable levels of public health research across public-health-relevant MRFF Initiatives and generally low proportions of primary and primordial prevention. A greater emphasis on primordial and primary prevention research in public-health-relevant Initiatives could advance prevention in Australia.
CONCLUSIONS: There appears to be scope for improvement in the prioritisation of upstream prevention research in public-health-relevant MRFF Initiatives and projects. Addressing this may enhance the benefit of MRFF to Australian public health.

A quality management system for clinical and public health research operations is indispensable because it ensures the integrity and reliability of research outcomes. By implementing a robust quality management practice in research implementation and operation, research teams can uphold the highest standard of research conduct, thereby enhancing the credibility and trustworthiness of research findings. This paper elucidates the significance and role of a quality management system in clinical and public health research operations and its efficacy in minimising and eliminating protocol deviations and highlights the key steps in setting up a quality management system for research operations.

OBJECTIVE: Associations between place and population health are of interest to researchers and policymakers. The objective of this paper is to explore, summarise and compare content across contemporary Australian geo-referenced population health survey data sets.
METHODS: A search for recent (2015 or later) population health surveys from within Australia containing geographic information from participants was conducted. Survey response frames were analysed and categorised based on demographic, risk factor and disease-related characteristics. Analysis using interactive Sankey diagrams shows the extent of content overlap and differences between population health surveys in Australia.
RESULTS: Thirteen Australian geo-referenced population health survey data sets were identified. Information captured across surveys was inconsistent as was the spatial granularity of respondent information. Health and demographic features most frequently captured were symptoms, signs and clinical findings from the International Statistical Classification of Diseases and Related Health Problems version 11, employment, housing, income, self-rated health and risk factors, including alcohol consumption, diet, medical treatments, physical activity and weight-related questions. Sankey diagrams were deployed online for use by public health researchers.
CONCLUSIONS: Identifying the relationship between place and health in Australia is made more difficult by inconsistencies in information collected across surveys deployed in different regions in Australia.
CONCLUSIONS: Public health research investigating place and health involves a vast and inconsistent patchwork of information within and across states, which may impact broad-scale research questions. The tools developed here assist public health researchers to identify surveys suitable for their research queries related to place and health.

BACKGROUND: The freelance economy has seen rapid growth worldwide in recent years and the Philippines is not an exception. Freelance workers are becoming increasingly common in healthcare and research. Early career researchers carry out most of scientific research and can play a critical role in advancing public health by bringing new perspectives and diversity to the field. Existing literature has mostly focused on the experiences of early career researchers in an institutional academic setting. This study aimed to understand the experiences of freelance early career researchers in the health policy and systems space in the Philippines.
METHODS: This qualitative study collected data from 18 to 22 March 2022 through virtual interview and focus group discussions. Themes and codes were created based on the topic guide developed. New themes and codes were generated as they emerged. Two researchers coded the data using both a priori and emergent codes. Any coding conflicts were resolved through discussions until intercoder agreement was reached. Interpretation and conclusions from the data were developed by 2 researchers with consideration for its context and relationship between themes.
RESULTS: Fifteen current and former freelance researchers participated in the study. Most are female, under 35 years old, and with an undergraduate degree as the highest educational attainment. The findings highlight insights and challenges faced by early career researchers in aspects of: (1) work arrangement, (2) tasks, (3) expectations from senior researchers, (4) development in the health policy and systems field, (5) relationship with peers, and (6) motivations for continuing to work as a freelance health policy and systems researcher.
CONCLUSIONS: This study reveals the challenges freelance early career researchers face, highlighting the need for enhanced support and recognition amidst rapidly evolving workforce demands and complex health dilemmas. Recommendations include structured mentorship, professional development, innovative funding models, and the establishment of a supportive network. Advocacy for policies ensuring freelancer inclusion in the economy and policy-making is crucial. Future research should investigate their experiences further, including their roles, transitions, and the impacts of funding trends, to foster their development and integration into public health research and policy.

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The routine data of all statutorily insured persons according to the Data Transparency Regulation (DaTraV data) represent a promising data source for the recurrent and timely surveillance of non-communicable diseases (NCDs) in Germany. Thereby, it has become apparent that there is a high demand for reference evaluations that enable quick and regularly repeatable analyses on important NCDs. Against this background, ReFern-01 was initiated, a joint project of the Robert Koch Institute (RKI) and the Federal Institute for Drugs and Medical Devices (BfArM). In collaboration with experts from the field of secondary data analysis and healthcare research, reference evaluations for estimating prevalence, incidence, and mortality for important public health-relevant diseases were developed. First, 11 central NCDs were selected by means of an online survey, and initial case definitions were created in conjunction with a literature review. These were then discussed and agreed upon in a virtual workshop. The created reference evaluations (analysis scripts) allow a standardized estimation of the mentioned epidemiological figures, which are comparable over time and regionally. In addition to providing the results, the scripts will be available at the BfArM for further analysis. Provided that remote access to the analysis of the DaTraV data is available in the future, the results of the ReFern project can strengthen the surveillance of NCDs and support public health actors, for example, in the planning and implementation of health promotion and prevention measures at the federal, state, county, and local levels.
UNASSIGNED: Die Routinedaten aller gesetzlich Krankenversicherten nach Datentransparenzverordnung (DaTraV-Daten) stellen eine vielversprechende Datenquelle für die wiederkehrende und zeitnahe Surveillance nicht-übertragbarer Erkrankungen (NCD) in Deutschland dar. Dabei hat sich gezeigt, dass ein hoher Bedarf für Referenzauswertungen besteht, die schnelle und regelmäßig wiederholbare Analysen zu wichtigen NCD ermöglichen. Vor diesem Hintergrund wurde „ReFern-01“ initiiert, ein gemeinsames Projekt vom Robert Koch-Institut (RKI) und dem Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM). In Zusammenarbeit mit Expert:innen aus dem Bereich der Sekundärdatenanalyse und Versorgungsforschung wurden Referenzauswertungen zur Schätzung von Prävalenz, Inzidenz und Mortalität für wichtige Public-Health-relevante Erkrankungen erarbeitet. Zunächst wurden mittels einer Onlinebefragung 11 zentrale NCD ausgewählt und in Zusammenschau mit einer Literaturrecherche initiale Falldefinitionen erstellt. Diese wurden anschließend in einem virtuellen Workshop diskutiert und konsentiert. Die erstellten Referenzauswertungen (Analyseskripte) ermöglichen eine standardisierte Schätzung der genannten epidemiologischen Kennzahlen, die über die Zeit und regional vergleichbar sind. Neben der Bereitstellung der Ergebnisse werden die Skripte am BfArM für zukünftige Datennutzende zur Verfügung stehen. Mit dem Fernzugang zur Analyse der DaTraV-Daten, der derzeit am Forschungsdatenzentrum Gesundheit (FDZ Gesundheit) aufgebaut wird, können die Ergebnisse des Projekts ReFern die Surveillance von NCD stärken und Public-Health-Akteur:innen beispielsweise bei der Planung und Umsetzung von Maßnahmen der Gesundheitsförderung und Prävention auf Ebene von Bund, Ländern, Kreisen und Kommunen unterstützen.

Informed consent procedures for large population-based cohort studies should be comprehensive and easy-to-use. This is particularly challenging when participants from different socio-economic groups and multicultural ethnic backgrounds are involved. Recently, more and more studies have tried to use multimedia in informed consent procedures. We describe the development and testing of a digital informed consent app and elaborate on whether this may contribute to a comprehensive and practical procedure to obtain informed consent for public health research.
In a sample of parents with young children, we used a mixed method approach to study the user experience of an informed consent app and evaluate whether it can be used to adequately inform people and register their consent. Through semi-structured interviews we investigated participants\' experiences with and opinions about the app, with a special focus on comprehensibility of the content and the usability of the app. Information retention questions were asked to evaluate to what extent participants could recall key aspects of the provided study information.
The 30 participants in this study used the app between 4 and 15 min to give their consent. Overall, they found the app well-designed, informative and easy to use. To learn more about the study for which informed consent is asked, most of the participants chose to watch the animated film, which was generally found to convey information in a clear manner. The identification process was met with mixed reactions, with some feeling it as a secure way to give consent, while for others it contradicted their view of using data anonymously. Information retention questions showed that while all participants remembered various aspects of the study, fewer than half answered all four questions satisfactorily.
Our study shows that a well-designed informed consent app can be an effective tool to inform eligible participants and to record consents. Still, some issues remain, including trust barriers towards the identification procedure and lack of information retention in some participants. When implementing consent procedures that incorporate digital formats, it may be beneficial to also invest in a complementary face-to-face recruitment approach.

BACKGROUND: Complex systems approaches are increasingly used in health promotion and noncommunicable disease prevention research, policy and practice. Questions emerge as to the best ways to take a complex systems approach, specifically with respect to population physical activity (PA). Using an Attributes Model is one way to understand complex systems. We aimed to examine the types of complex systems methods used in current PA research and identify what methods align with a whole system approach as reflected by an Attributes Model.
METHODS: A scoping review was conducted and two databases were searched. Twenty-five articles were selected and data analysis was based upon the following: the complex systems research methods used, research aims, if participatory methods were used and evidence of discussion regarding attributes of systems.
RESULTS: There were three groups of methods used: system mapping, simulation modelling and network analysis. System mapping methods appeared to align best with a whole system approach to PA promotion because they largely aimed to understand complex systems, examined interactions and feedback among variables, and used participatory methods. Most of these articles focused on PA (as opposed to integrated studies). Simulation modelling methods were largely focused on examining complex problems and identifying interventions. These methods did not generally focus on PA or use participatory methods. While network analysis articles focused on examining complex systems and identifying interventions, they did not focus on PA nor use participatory methods. All attributes were discussed in some way in the articles. Attributes were explicitly reported on in terms of findings or were part of discussion and conclusion sections. System mapping methods appear to be well aligned with a whole system approach because these methods addressed all attributes in some way. We did not find this pattern with other methods.
CONCLUSIONS: Future research using complex systems methods may benefit from applying the Attributes Model in conjunction with system mapping methods. Simulation modelling and network analysis methods are seen as complementary and could be used when system mapping methods identify priorities for further investigation (e.g. what interventions to implement or how densely connected relationships are in systems).

The COVID-19 pandemic has further deepened socioeconomic and health inequities worldwide, especially among populations experiencing social vulnerability, such as international migrants. Sustained lockdowns and social distancing have raised challenges to conducting public health research with hard-to-reach populations. This study aims at exploring strategies to recruit \"hard-to-reach\" international migrants for qualitative public health research during the pandemic in Chile, based on the authors\' experience. A retrospective qualitative evaluation process was carried out on the recruitment processes of three qualitative research projects focused on international migrants in Chile. All projects were implemented during the COVID-19 pandemic, demanding complementary and flexible strategies: (i) social media; (ii) snowball sampling; (iii) referrals from social workers and pro-migrant and migrant-led organizations; (iv) vaccination centers and healthcare centers; and (v) community-based recruitment. The strategies are qualitatively evaluated around seven emerging qualitative categories: (i) feasibility during lockdown periods; (ii) speed of recruitment; (iii) geographical coverage; (iv) sample diversity; (v) proportion of successful interviews; (vi) ethical considerations; and (vii) cost. Engaging hard-to-reach international migrants in public health research during the pandemic required constantly adapting recruitment strategies. Furthermore, relying on strategies that were not only Internet-based promoted the participation of populations with limited access to the Internet and low-digital literacy.

Much research is being carried out using publicly available Twitter data in the field of public health, but the types of research questions that these data are being used to answer and the extent to which these projects require ethical oversight are not clear.
This review describes the current state of public health research using Twitter data in terms of methods and research questions, geographic focus, and ethical considerations including obtaining informed consent from Twitter handlers.
We implemented a systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, of articles published between January 2006 and October 31, 2019, using Twitter data in secondary analyses for public health research, which were found using standardized search criteria on SocINDEX, PsycINFO, and PubMed. Studies were excluded when using Twitter for primary data collection, such as for study recruitment or as part of a dissemination intervention.
We identified 367 articles that met eligibility criteria. Infectious disease (n=80, 22%) and substance use (n=66, 18%) were the most common topics for these studies, and sentiment mining (n=227, 62%), surveillance (n=224, 61%), and thematic exploration (n=217, 59%) were the most common methodologies employed. Approximately one-third of articles had a global or worldwide geographic focus; another one-third focused on the United States. The majority (n=222, 60%) of articles used a native Twitter application programming interface, and a significant amount of the remainder (n=102, 28%) used a third-party application programming interface. Only one-third (n=119, 32%) of studies sought ethical approval from an institutional review board, while 17% of them (n=62) included identifying information on Twitter users or tweets and 36% of them (n=131) attempted to anonymize identifiers. Most studies (n=272, 79%) included a discussion on the validity of the measures and reliability of coding (70% for interreliability of human coding and 70% for computer algorithm checks), but less attention was paid to the sampling frame, and what underlying population the sample represented.
Twitter data may be useful in public health research, given its access to publicly available information. However, studies should exercise greater caution in considering the data sources, accession method, and external validity of the sampling frame. Further, an ethical framework is necessary to help guide future research in this area, especially when individual, identifiable Twitter users and tweets are shared and discussed.
PROSPERO CRD42020148170; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=148170.