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Roberts MC, Holt KE, Del Fiol G, Baccarelli AA, Allen CG. Precision public health in the era of genomics and big data. Nat Med 2024; 30:1865-1873. [PMID: 38992127 DOI: 10.1038/s41591-024-03098-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/29/2024] [Indexed: 07/13/2024]
Abstract
Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.
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Affiliation(s)
- Megan C Roberts
- Division of Pharmaceutical Outcomes and Policy, University of North Carolina Eshelman School of Pharmacy, Chapel Hill, NC, USA.
| | - Kathryn E Holt
- Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, UK
- Department of Infectious Diseases, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Guilherme Del Fiol
- Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Andrea A Baccarelli
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Caitlin G Allen
- Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
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Mess F, Blaschke S, Schick TS, Friedrich J. Precision prevention in worksite health-A scoping review on research trends and gaps. PLoS One 2024; 19:e0304951. [PMID: 38857277 PMCID: PMC11164362 DOI: 10.1371/journal.pone.0304951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 05/22/2024] [Indexed: 06/12/2024] Open
Abstract
OBJECTIVES To map the current state of precision prevention research in the workplace setting, specifically to study contexts and characteristics, and to analyze the precision prevention approach in the stages of risk assessment/data monitoring, data analytics, and the health promotion interventions implemented. METHODS Six international databases were searched for studies published between January 2010 and May 2023, using the term "precision prevention" or its synonyms in the context of worksite health promotion. RESULTS After screening 3,249 articles, 129 studies were reviewed. Around three-quarters of the studies addressed an intervention (95/129, 74%). Only 14% (18/129) of the articles primarily focused on risk assessment and data monitoring, and 12% of the articles (16/129) mainly included data analytics studies. Most of the studies focused on behavioral outcomes (61/160, 38%), followed by psychological (37/160, 23%) and physiological (31/160, 19%) outcomes of health (multiple answers were possible). In terms of study designs, randomized controlled trials were used in more than a third of all studies (39%), followed by cross-sectional studies (18%), while newer designs (e.g., just-in-time-adaptive-interventions) are currently rarely used. The main data analyses of all studies were regression analyses (44% with analyses of variance or linear mixed models), whereas machine learning methods (e.g., Algorithms, Markov Models) were conducted only in 8% of the articles. DISCUSSION Although there is a growing number of precision prevention studies in the workplace, there are still research gaps in applying new data analysis methods (e.g., machine learning) and implementing innovative study designs. In the future, it is desirable to take a holistic approach to precision prevention in the workplace that encompasses all the stages of precision prevention (risk assessment/data monitoring, data analytics and interventions) and links them together as a cycle.
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Affiliation(s)
- Filip Mess
- Technical University of Munich, TUM School of Medicine and Health, Munich, Germany
| | - Simon Blaschke
- Technical University of Munich, TUM School of Medicine and Health, Munich, Germany
| | - Teresa S. Schick
- Technical University of Munich, TUM School of Medicine and Health, Munich, Germany
| | - Julian Friedrich
- Technical University of Munich, TUM School of Medicine and Health, Munich, Germany
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De La Cerda I, Bauer CX, Zhang K, Lee M, Jones M, Rodriguez A, McCormick JB, Fisher-Hoch SP. Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health. JMIR Public Health Surveill 2023; 9:e47981. [PMID: 38117549 PMCID: PMC10765283 DOI: 10.2196/47981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 08/18/2023] [Accepted: 10/17/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Cameron County, a low-income south Texas-Mexico border county marked by severe health disparities, was consistently among the top counties with the highest COVID-19 mortality in Texas at the onset of the pandemic. The disparity in COVID-19 burden within Texas counties revealed the need for effective interventions to address the specific needs of local health departments and their communities. Publicly available COVID-19 surveillance data were not sufficiently timely or granular to deliver such targeted interventions. An agency-academic collaboration in Cameron used novel geographic information science methods to produce granular COVID-19 surveillance data. These data were used to strategically target an educational outreach intervention named "Boots on the Ground" (BOG) in the City of Brownsville (COB). OBJECTIVE This study aimed to evaluate the impact of a spatially targeted community intervention on daily COVID-19 test counts. METHODS The agency-academic collaboration between the COB and UTHealth Houston led to the creation of weekly COVID-19 epidemiological reports at the census tract level. These reports guided the selection of census tracts to deliver targeted BOG between April 21 and June 8, 2020. Recordkeeping of the targeted BOG tracts and the intervention dates, along with COVID-19 daily testing counts per census tract, provided data for intervention evaluation. An interrupted time series design was used to evaluate the impact on COVID-19 test counts 2 weeks before and after targeted BOG. A piecewise Poisson regression analysis was used to quantify the slope (sustained) and intercept (immediate) change between pre- and post-BOG COVID-19 daily test count trends. Additional analysis of COB tracts that did not receive targeted BOG was conducted for comparison purposes. RESULTS During the intervention period, 18 of the 48 COB census tracts received targeted BOG. Among these, a significant change in the slope between pre- and post-BOG daily test counts was observed in 5 tracts, 80% (n=4) of which had a positive slope change. A positive slope change implied a significant increase in daily COVID-19 test counts 2 weeks after targeted BOG compared to the testing trend observed 2 weeks before intervention. In an additional analysis of the 30 census tracts that did not receive targeted BOG, significant slope changes were observed in 10 tracts, of which positive slope changes were only observed in 20% (n=2). In summary, we found that BOG-targeted tracts had mostly positive daily COVID-19 test count slope changes, whereas untargeted tracts had mostly negative daily COVID-19 test count slope changes. CONCLUSIONS Evaluation of spatially targeted community interventions is necessary to strengthen the evidence base of this important approach for local emergency preparedness. This report highlights how an academic-agency collaboration established and evaluated the impact of a real-time, targeted intervention delivering precision public health to a small community.
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Affiliation(s)
- Isela De La Cerda
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States
| | - Cici X Bauer
- Department of Biostatistics and Data Science, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Kehe Zhang
- Department of Biostatistics and Data Science, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Miryoung Lee
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States
| | - Michelle Jones
- Public Health Department, City of Brownsville, Brownsville, TX, United States
| | - Arturo Rodriguez
- Public Health Department, City of Brownsville, Brownsville, TX, United States
| | - Joseph B McCormick
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States
| | - Susan P Fisher-Hoch
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States
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Baker JL, Bjerregaard LG. Advancing precision public health for obesity in children. Rev Endocr Metab Disord 2023; 24:1003-1010. [PMID: 37055611 PMCID: PMC10101815 DOI: 10.1007/s11154-023-09802-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/12/2023] [Indexed: 04/15/2023]
Abstract
Worldwide, far too many children and adolescents are living with the disease of obesity. Despite decades of public health initiatives, rates are still rising in many countries. This raises the question of whether precision public health may be a more successful approach to preventing obesity in youth. In this review, the objective was to review the literature on precision public health in the context of childhood obesity prevention and to discuss how precision public health may advance the field of childhood obesity prevention. As precision public health is a concept that is still evolving and not fully identifiable in the literature, a lack of published studies precluded a formal review. Therefore, the approach of using a broad interpretation of precision public health was used and recent advances in childhood obesity research in the areas of surveillance and risk factor identification as well as intervention, evaluation and implementation using selected studies were summarized. Encouragingly, big data from a multitude of designed and organic sources are being used in new and innovative ways to provide more granular surveillance and risk factor identification in obesity in children. Challenges were identified in terms of data access, completeness, and integration, ensuring inclusion of all members of society, ethics, and translation to policy. As precision public health advances, it may yield novel insights that can contribute to strong policies acting in concert that ultimately lead to the prevention of obesity in children.
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Affiliation(s)
- Jennifer L Baker
- Center for Clinical Research and Prevention, Copenhagen University Hospital- Bispebjerg and Frederiksberg, Frederiksberg, Denmark.
| | - Lise G Bjerregaard
- Center for Clinical Research and Prevention, Copenhagen University Hospital- Bispebjerg and Frederiksberg, Frederiksberg, Denmark
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Mauch CE, Edney SM, Viana JNM, Gondalia S, Sellak H, Boud SJ, Nixon DD, Ryan JC. Precision health in behaviour change interventions: A scoping review. Prev Med 2022; 163:107192. [PMID: 35963310 DOI: 10.1016/j.ypmed.2022.107192] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 07/24/2022] [Accepted: 08/07/2022] [Indexed: 11/09/2022]
Abstract
Precision health seeks to optimise behavioural interventions by delivering personalised support to those in need, when and where they need it. Conceptualised a decade ago, progress toward this vision of personally relevant and effective population-wide interventions continues to evolve. This scoping review aimed to map the state of precision health behaviour change intervention research. This review included studies from a broader precision health review. Six databases were searched for studies published between January 2010 and June 2020, using the terms 'precision health' or its synonyms, and including an intervention targeting modifiable health behaviour(s) that was evaluated experimentally. Thirty-one studies were included, 12 being RCTs (39%), and 17 with weak study design (55%). Most interventions targeted physical activity (27/31, 87%) and/or diet (24/31, 77%), with 74% (23/31) targeting two to four health behaviours. Interventions were personalised via human interaction in 55% (17/31) and digitally in 35% (11/31). Data used for personalising interventions was largely self-reported, by survey or diary (14/31, 45%), or digitally (14/31, 45%). Data was mostly behavioural or lifestyle (20/31, 65%), and physiologic, biochemical or clinical (15/31, 48%), with no studies utilising genetic/genomic data. This review demonstrated that precision health behaviour change interventions remain dependent on human-led, low-tech personalisation, and have not fully considered the interaction between behaviour and the social and environmental contexts of individuals. Further research is needed to understand the relationship between personalisation and intervention effectiveness, working toward the development of sophisticated and scalable behaviour change interventions that have tangible public health impact.
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Affiliation(s)
- Chelsea E Mauch
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, SA, Australia.
| | - Sarah M Edney
- Physical Activity and Nutrition Determinants in Asia (PANDA) Programme, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
| | - John Noel M Viana
- Responsible Innovation Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia; Australian National Centre for the Public Awareness of Science, Australian National University, Canberra, ACT, Australia.
| | - Shakuntla Gondalia
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, SA, Australia; Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, SA, Australia; Centre for Human Psychopharmacology, Swinburne University of Technology, Melbourne, VC, Australia..
| | - Hamza Sellak
- Data61, Commonwealth Scientific and Industrial Research Organisation, Melbourne, VC, Australia.
| | - Sarah J Boud
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Dakota D Nixon
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Jillian C Ryan
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, SA, Australia; Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, SA, Australia; School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia.
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Kobayashi S, Sata F, Kishi R. Gene-environment interactions related to maternal exposure to environmental and lifestyle-related chemicals during pregnancy and the resulting adverse fetal growth: a review. Environ Health Prev Med 2022; 27:24. [PMID: 35675978 PMCID: PMC9251623 DOI: 10.1265/ehpm.21-00033] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Background There are only limited numbers of reviews on the association of maternal-child genetic polymorphisms and environmental and lifestyle-related chemical exposure during pregnancy with adverse fetal growth. Thus, this article aims to review: (1) the effect of associations between the above highlighted factors on adverse fetal growth and (2) recent birth cohort studies regarding environmental health risks. Methods Based on a search of the PubMed database through August 2021, 68 epidemiological studies on gene-environment interactions, focusing on the association between environmental and lifestyle-related chemical exposure and adverse fetal growth was identified. Moreover, we also reviewed recent worldwide birth cohort studies regarding environmental health risks. Results Thirty studies examined gene-smoking associations with adverse fetal growth. Sixteen maternal genes significantly modified the association between maternal smoking and adverse fetal growth. Two genes significantly related with this association were detected in infants. Moreover, the maternal genes that significantly interacted with maternal smoking during pregnancy were cytochrome P450 1A1 (CYP1A1), X-ray repair cross-complementing protein 3 (XRCC3), interleukin 6 (IL6), interleukin 1 beta (IL1B), human leukocyte antigen (HLA) DQ alpha 1 (HLA-DQA1), HLA DQ beta 1 (HLA-DQB1), and nicotinic acetylcholine receptor. Fetal genes that had significant interactions with maternal smoking during pregnancy were glutathione S-transferase theta 1 (GSTT1) and fat mass and obesity-associated protein (FTO). Thirty-eight studies examined the association between chemical exposures and adverse fetal growth. In 62 of the 68 epidemiological studies (91.2%), a significant association was found with adverse fetal growth. Across the studies, there was a wide variation in the analytical methods used, especially with respect to the genetic polymorphisms of interest, environmental and lifestyle-related chemicals examined, and the study design used to estimate the gene-environment interactions. It was also found that a consistently increasing number of European and worldwide large-scale birth cohort studies on environmental health risks have been conducted since approximately 1996. Conclusion There is some evidence to suggest the importance of gene-environment interactions on adverse fetal growth. The current knowledge on gene-environment interactions will help guide future studies on the combined effects of maternal-child genetic polymorphisms and exposure to environmental and lifestyle-related chemicals during pregnancy. Supplementary information The online version contains supplementary material available at https://doi.org/10.1265/ehpm.21-00033.
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Affiliation(s)
| | - Fumihiro Sata
- Center for Environmental and Health Sciences, Hokkaido University.,Health Center, Chuo University
| | - Reiko Kishi
- Center for Environmental and Health Sciences, Hokkaido University
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Rieckmann A, Dworzynski P, Arras L, Lapuschkin S, Samek W, Arah OA, Rod NH, Ekstrøm CT. Causes of Outcome Learning: a causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. Int J Epidemiol 2022; 51:1622-1636. [PMID: 35526156 PMCID: PMC9799206 DOI: 10.1093/ije/dyac078] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 04/12/2022] [Indexed: 01/07/2023] Open
Abstract
Nearly all diseases are caused by different combinations of exposures. Yet, most epidemiological studies focus on estimating the effect of a single exposure on a health outcome. We present the Causes of Outcome Learning approach (CoOL), which seeks to discover combinations of exposures that lead to an increased risk of a specific outcome in parts of the population. The approach allows for exposures acting alone and in synergy with others. The road map of CoOL involves (i) a pre-computational phase used to define a causal model; (ii) a computational phase with three steps, namely (a) fitting a non-negative model on an additive scale, (b) decomposing risk contributions and (c) clustering individuals based on the risk contributions into subgroups; and (iii) a post-computational phase on hypothesis development, validation and triangulation using new data before eventually updating the causal model. The computational phase uses a tailored neural network for the non-negative model on an additive scale and layer-wise relevance propagation for the risk decomposition through this model. We demonstrate the approach on simulated and real-life data using the R package 'CoOL'. The presentation focuses on binary exposures and outcomes but can also be extended to other measurement types. This approach encourages and enables researchers to identify combinations of exposures as potential causes of the health outcome of interest. Expanding our ability to discover complex causes could eventually result in more effective, targeted and informed interventions prioritized for their public health impact.
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Affiliation(s)
- Andreas Rieckmann
- Corresponding author. Section of Epidemiology, Department of Public Health, University of Copenhagen, Øster Farimagsgade 5, DK-1353 Copenhagen K, Denmark. E-mail:
| | - Piotr Dworzynski
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Leila Arras
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - Sebastian Lapuschkin
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - Wojciech Samek
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany,BIFOLD—Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
| | - Onyebuchi Aniweta Arah
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, USA,Department of Statistics, UCLA College of Letters and Science, Los Angeles, CA, USA
| | - Naja Hulvej Rod
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Claus Thorn Ekstrøm
- Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
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Canfell OJ, Davidson K, Woods L, Sullivan C, Cocoros NM, Klompas M, Zambarano B, Eakin E, Littlewood R, Burton-Jones A. Precision Public Health for Non-communicable Diseases: An Emerging Strategic Roadmap and Multinational Use Cases. Front Public Health 2022; 10:854525. [PMID: 35462850 PMCID: PMC9024120 DOI: 10.3389/fpubh.2022.854525] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/18/2022] [Indexed: 12/14/2022] Open
Abstract
Non-communicable diseases (NCDs) remain the largest global public health threat. The emerging field of precision public health (PPH) offers a transformative opportunity to capitalize on digital health data to create an agile, responsive and data-driven public health system to actively prevent NCDs. Using learnings from digital health, our aim is to propose a vision toward PPH for NCDs across three horizons of digital health transformation: Horizon 1—digital public health workflows; Horizon 2—population health data and analytics; Horizon 3—precision public health. This perspective provides a high-level strategic roadmap for public health practitioners and policymakers, health system stakeholders and researchers to achieving PPH for NCDs. Two multinational use cases are presented to contextualize our roadmap in pragmatic action: ESP and RiskScape (USA), a mature PPH platform for multiple NCDs, and PopHQ (Australia), a proof-of-concept population health informatics tool to monitor and prevent obesity. Our intent is to provide a strategic foundation to guide new health policy, investment and research in the rapidly emerging but nascent area of PPH to reduce the public health burden of NCDs.
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Affiliation(s)
- Oliver J. Canfell
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, Brisbane, QLD, Australia
- Digital Health Cooperative Research Centre, Australian Government, Sydney, NSW, Australia
- Health and Wellbeing Queensland, Queensland Government, The State of Queensland, Brisbane, QLD, Australia
- *Correspondence: Oliver J. Canfell
| | - Kamila Davidson
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, Brisbane, QLD, Australia
| | - Leanna Woods
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Digital Health Cooperative Research Centre, Australian Government, Sydney, NSW, Australia
| | - Clair Sullivan
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Health and Wellbeing Queensland, Queensland Government, The State of Queensland, Brisbane, QLD, Australia
- Metro North Hospital and Health Service, Department of Health, Queensland Government, Herston, QLD, Australia
| | - Noelle M. Cocoros
- Department of Population Medicine at Harvard Medical School and the Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Michael Klompas
- Department of Population Medicine at Harvard Medical School and the Harvard Pilgrim Health Care Institute, Boston, MA, United States
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States
| | - Bob Zambarano
- Commonwealth Informatics Inc., Waltham, MA, United States
| | - Elizabeth Eakin
- School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Robyn Littlewood
- Health and Wellbeing Queensland, Queensland Government, The State of Queensland, Brisbane, QLD, Australia
| | - Andrew Burton-Jones
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, Brisbane, QLD, Australia
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Bosward R, Braunack-Mayer A, Frost E, Carter S. Mapping precision public health definitions, terminology and applications: a scoping review protocol. BMJ Open 2022; 12:e058069. [PMID: 35197357 PMCID: PMC8867336 DOI: 10.1136/bmjopen-2021-058069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
INTRODUCTION Precision public health is an emerging and evolving field. Academic communities are divided regarding terminology and definitions, and what the scope, parameters and goals of precision public health should include. This protocol summarises the procedure for a scoping review which aims to identify and describe definitions, terminology, uses of the term and concepts in current literature. METHODS AND ANALYSIS A scoping review will be undertaken to gather existing literature on precision public health. We will search CINAHL, PubMed, Scopus, Web of Science and Google Scholar, and include all documents published in English that mention precision public health. A critical discourse analysis of the resulting papers will generate an account of precision public health terminology, definitions and uses of the term and the use and meaning of language. The analysis will occur in stages: first, descriptive information will be extracted and descriptive statistics will be calculated in order to characterise the literature. Second, occurrences of the phrase 'precision public health' and alternative terms in documents will be enumerated and mapped, and definitions collected. The third stage of discourse analysis will involve analysis and interpretation of the meaning of precision public health, including the composition, organisation and function of discourses. Finally, discourse analysis of alternative phrases to precision public health will be undertaken. This will include analysis and interpretation of what alternative phrases to precision public health are used to mean, how the phrases relate to each other and how they are compared or contrasted to precision public health. Results will be grouped under headings according to how they answer the research questions. ETHICS AND DISSEMINATION No ethical approval will be required for the scoping review. Results of the scoping review will be used as part of a doctoral thesis, and may be published in journals, conference proceedings or elsewhere.
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Affiliation(s)
- Rebecca Bosward
- Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
| | - Annette Braunack-Mayer
- Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
| | - Emma Frost
- Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
| | - Stacy Carter
- Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
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Edney SM, Park SH, Tan L, Chua XH, Dickens BSL, Rebello SA, Petrunoff N, Müller AM, Tan CS, Müller-Riemenschneider F, van Dam RM. Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). Digit Health 2022; 8:20552076221110534. [PMID: 35795338 PMCID: PMC9251970 DOI: 10.1177/20552076221110534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/13/2022] [Indexed: 11/17/2022] Open
Abstract
Background Modifiable risk factors for non-communicable diseases, including eating an unhealthy diet and being physically inactive, are influenced by complex and dynamic interactions between people and their social and physical environment. Therefore, understanding patterns and determinants of these risk factors as they occur in real life is essential to enable the design of precision public health interventions. Objective This paper describes the protocol for the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). The study uses real-time data capture methods to gain a comprehensive understanding of eating and movement behaviours, including how these differ by socio-demographic characteristics and are shaped by people's interaction with their social and physical environment. Methods COBRA is an observational study in free-living conditions. We will recruit 1500 adults aged 21-69 years from a large prospective cohort study. Real-time data capture methods will be used for nine consecutive days: an ecological momentary assessment app with a global positioning system enabled to collect location data, accelerometers to measure movement, and wearable sensors to monitor blood glucose levels. Participants receive six EMA surveys per day between 8 a.m. and 9.30 p.m. to capture information on behavioural risk factors including eating behaviours and diet composition movement behaviours (physical activity, sedentary behaviour, sleep), and related contextual factors. The second wave of ecological momentary assessment surveys with a global positioning system enabled will be sent 6 months later. Data will be analysed using generalised linear models to examine associations between behavioural risk factors and contextual determinants. Discussion Findings from this study will advance our understanding of dietary and movement behaviours as they occur in real-life and inform the development of personalised interventions to prevent chronic diseases.
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Affiliation(s)
- Sarah Martine Edney
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Su Hyun Park
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Linda Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Xin Hui Chua
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Borame Sue Lee Dickens
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Salome A Rebello
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Nick Petrunoff
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Andre Matthias Müller
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Cheun Seng Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Falk Müller-Riemenschneider
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Digital Health Center, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Departments of Exercise and Nutrition Sciences and Epidemiology, Milken Institute of Public Health, The George Washington University, Washington, DC, USA
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11
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Bickman L. Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health. ADMINISTRATION AND POLICY IN MENTAL HEALTH AND MENTAL HEALTH SERVICES RESEARCH 2021; 47:795-843. [PMID: 32715427 PMCID: PMC7382706 DOI: 10.1007/s10488-020-01065-8] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
This conceptual paper describes the current state of mental health services, identifies critical problems, and suggests how to solve them. I focus on the potential contributions of artificial intelligence and precision mental health to improving mental health services. Toward that end, I draw upon my own research, which has changed over the last half century, to highlight the need to transform the way we conduct mental health services research. I identify exemplars from the emerging literature on artificial intelligence and precision approaches to treatment in which there is an attempt to personalize or fit the treatment to the client in order to produce more effective interventions.
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Affiliation(s)
- Leonard Bickman
- Center for Children and Families; Psychology, Academic Health Center 1, Florida International University, 11200 Southwest 8th Street, Room 140, Miami, FL, 33199, USA.
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12
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da Silva RGL, Chammas R, Novaes HMD. Rethinking approaches of science, technology, and innovation in healthcare during the COVID-19 pandemic: the challenge of translating knowledge infrastructures to public needs. Health Res Policy Syst 2021; 19:104. [PMID: 34289860 PMCID: PMC8293568 DOI: 10.1186/s12961-021-00760-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 07/12/2021] [Indexed: 01/17/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) outbreak made it clear that despite the potential of science, technology, and innovation (ST&I) to positively impact healthcare systems worldwide, as shown by the rapid development of SARS-CoV-2 test diagnostics and new mRNA vaccines, healthcare stakeholders have faced significant challenges in responding to the crisis through well-integrated ST&I-oriented health initiatives and policies. Therefore, the pandemic has mobilized experts, industry, and governments to evaluate alternative trajectories to promote a more efficient dialogue between ST&I and public health. This article presents a critical thinking about the contemporary asymmetries in the technical and political infrastructures available for particular approaches in ST&I in health, such as precision medicine, and for public health systems worldwide, uncovering a persistent gap in the translation of knowledge and technologies to adequately coordinated responses to the pandemic. We stimulate the understanding of this process as a matter of translation between platforms of knowledge and policy rationales shaped by different institutionalized frames of organizational practices and agendas. We draw attention to the need to strengthen governance tools for the promotion of ST&I as a strategic component of the post-pandemic agenda in public health, to prepare societies to respond efficiently to future emergencies.
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Affiliation(s)
- Renan Gonçalves Leonel da Silva
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, Institute of Translational Medicine, Eidgenössische Technische Hochschule ETH Zürich, Zürich, Switzerland
| | - Roger Chammas
- Centro de Investigação Translacional em Oncologia, Faculdade de Medicina, Instituto do Câncer do Estado de São Paulo, Universidade de São Paulo, São Paulo, Brazil
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13
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Johnson WG. Using Precision Public Health to Manage Climate Change: Opportunities, Challenges, and Health Justice. THE JOURNAL OF LAW, MEDICINE & ETHICS : A JOURNAL OF THE AMERICAN SOCIETY OF LAW, MEDICINE & ETHICS 2020; 48:681-693. [PMID: 33404333 DOI: 10.1177/1073110520979374] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Amid public health concerns over climate change, "precision public health" (PPH) is emerging in next generation approaches to practice. These novel methods promise to augment public health operations by using ever larger and more robust health datasets combined with new tools for collecting and analyzing data. Precision strategies to protecting the public health could more effectively or efficiently address the systemic threats of climate change, but may also propagate or exacerbate health disparities for the populations most vulnerable in a changing climate. How PPH interventions collect and aggregate data, decide what to measure, and analyze data pose potential issues around privacy, neglecting social determinants of health, and introducing algorithmic bias into climate responses. Adopting a health justice framework, guided by broader social and climate justice tenets, can reveal principles and policy actions which may guide more responsible implementation of PPH in climate responses.
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Affiliation(s)
- Walter G Johnson
- Walter G. Johnson, J.D. M.S.T.P., is a research fellow at the Sandra Day O'Connor College of Law, Arizona State University. He received a J.D. from the Sandra Day O'Connor College of Law in 2020 and a Master of Science and Technology Policy (M.S.T.P.) from Arizona State University in 2017
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14
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Fernandes A, Van Lenthe FJ, Vallée J, Sueur C, Chaix B. Linking physical and social environments with mental health in old age: a multisensor approach for continuous real-life ecological and emotional assessment. J Epidemiol Community Health 2020; 75:477-483. [PMID: 33148684 PMCID: PMC8053354 DOI: 10.1136/jech-2020-214274] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 06/12/2020] [Accepted: 06/25/2020] [Indexed: 01/01/2023]
Abstract
Background Urban stress is mentioned as a plausible mechanism leading to chronic stress, which is a risk factor of depression. Yet, an accurate assessment of urban stressors in environmental epidemiology requires new methods. This article discusses methods for the sensor-based continuous assesment of geographic environments, stress and depressive symptoms in older age. We report protocols of the promoting mental well-being and healthy ageing in cities (MINDMAP) and Healthy Aging and Networks in Cities (HANC) studies nested in the RECORD Cohort as a background for a broad discussion about the theoretical foundation and monitoring tools of mobile sensing research in older age. Specifically, these studies allow one to compare how older people with and without depression perceive, navigate and use their environment; and how the built environments, networks of social contacts, and spatial mobility patterns influence the mental health of older people. Methods Our research protocol combines (1) Global Positioning System (GPS) and accelerometer tracking and a GPS-based mobility survey to assess participants’ mobility patterns, activity patterns and environmental exposures; (2) proximity detection to assess whether household members are close to each other; (3) ecological momentary assessment to track momentary mood and stress and environmental perceptions; and (4) electrodermal activity for the tentative prediction of stress. Data will be compared within individuals (at different times) and between persons with and without depressive symptoms. Conclusion The development of mobile sensing and survey technologies opens an avenue to improve understanding of the role of momentary stressors and resourcing features of residential and non-residential environments for older populations’ mental health. However, validation, privacy and ethical aspects are important issues to consider.
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Affiliation(s)
- Amanda Fernandes
- INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Nemesis Research Team, Sorbonne Université, Paris, France
| | - Frank J Van Lenthe
- Department of Public Health, Erasmus University Medical Center, Rotterdam, Netherlands.,Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, Netherlands
| | - Julie Vallée
- UMR Géographie-cités, Centre National de la Recherche Scientifique, Paris, France
| | - Cedric Sueur
- CNRS, IPHC UMR 7178, Université de Strasbourg, Strasbourg, France.,Institut Universitaire de France, Paris, France
| | - Basile Chaix
- INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Nemesis Research Team, Sorbonne Université, Paris, France
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15
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Sariola S, Gilbert SF. Toward a Symbiotic Perspective on Public Health: Recognizing the Ambivalence of Microbes in the Anthropocene. Microorganisms 2020; 8:E746. [PMID: 32429344 PMCID: PMC7285259 DOI: 10.3390/microorganisms8050746] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 05/13/2020] [Accepted: 05/14/2020] [Indexed: 02/07/2023] Open
Abstract
Microbes evolve in complex environments that are often fashioned, in part, by human desires. In a global perspective, public health has played major roles in structuring how microbes are perceived, cultivated, and destroyed. The germ theory of disease cast microbes as enemies of the body and the body politic. Antibiotics have altered microbial development by providing stringent natural selection on bacterial species, and this has led to the formation of antibiotic-resistant bacterial strains. Public health perspectives such as "Precision Public Health" and "One Health" have recently been proposed to further manage microbial populations. However, neither of these take into account the symbiotic relationships that exist between bacterial species and between bacteria, viruses, and their eukaryotic hosts. We propose a perspective on public health that recognizes microbial evolution through symbiotic associations (the hologenome theory) and through lateral gene transfer. This perspective has the advantage of including both the pathogenic and beneficial interactions of humans with bacteria, as well as combining the outlook of the "One Health" model with the genomic methodologies utilized in the "Precision Public Health" model. In the Anthropocene, the conditions for microbial evolution have been altered by human interventions, and public health initiatives must recognize both the beneficial (indeed, necessary) interactions of microbes with their hosts as well as their pathogenic interactions.
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Affiliation(s)
- Salla Sariola
- Faculty of Social Sciences, Sociology, University of Helsinki, 00014 Helsinki, Finland;
| | - Scott F. Gilbert
- Department of Biology, Swarthmore College, Swarthmore, PA 19081, USA
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