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Hossain MB, LaMunion SR, Crouter SE, Melanson EL, Sazonov E. A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor. SENSORS (BASEL, SWITZERLAND) 2024; 24:3046. [PMID: 38793899 PMCID: PMC11125058 DOI: 10.3390/s24103046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/04/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024]
Abstract
Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and energy expenditure (EE) estimation. Traditionally, sensors are attached to the hip or wrist. The primary aim of this research is to investigate the use of an eyeglass-mounted wearable energy intake sensor (Automatic Ingestion Monitor v2, AIM-2) for simultaneous recognition of physical activity (PAR) and estimation of steady-state EE as compared to a traditional hip-worn device. Study data were collected from six participants performing six structured activities, with the reference EE measured using indirect calorimetry (COSMED K5) and reported as metabolic equivalents of tasks (METs). Next, a novel deep convolutional neural network-based multitasking model (Multitasking-CNN) was developed for PAR and EE estimation. The Multitasking-CNN was trained with a two-step progressive training approach for higher accuracy, where in the first step the model for PAR was trained, and in the second step the model was fine-tuned for EE estimation. Finally, the performance of Multitasking-CNN on AIM-2 attached to eyeglasses was compared to the ActiGraph GT9X (AG) attached to the right hip. On the AIM-2 data, Multitasking-CNN achieved a maximum of 95% testing accuracy of PAR, a minimum of 0.59 METs mean square error (MSE), and 11% mean absolute percentage error (MAPE) in EE estimation. Conversely, on AG data, the Multitasking-CNN model achieved a maximum of 82% testing accuracy in PAR, a minimum of 0.73 METs MSE, and 13% MAPE in EE estimation. These results suggest the feasibility of using an eyeglass-mounted sensor for both PAR and EE estimation.
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Affiliation(s)
- Md Billal Hossain
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA;
| | - Samuel R. LaMunion
- Department of Kinesiology, Recreation and Sport Studies, The University of Tennessee, Knoxville, TN 37996, USA; (S.R.L.); (S.E.C.)
| | - Scott E. Crouter
- Department of Kinesiology, Recreation and Sport Studies, The University of Tennessee, Knoxville, TN 37996, USA; (S.R.L.); (S.E.C.)
| | - Edward L. Melanson
- USA Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Edward Sazonov
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA;
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Qiao H, Zhang J. Enhancing global thinking can reduce the misconception of accumulation: A potential way to mitigate climate change. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:58618-58629. [PMID: 36988801 DOI: 10.1007/s11356-023-26510-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 03/13/2023] [Indexed: 05/10/2023]
Abstract
Climate change and global warming have long been attention and concern all over the world. However, there is always a debate about when and to what degree to take action like reducing carbon dioxide emissions. Recently, researchers found that the public has misconceptions about climate dynamics, which might be a reason for people do not support prompt mitigation of greenhouse gas emissions. The core problem of misconceptions is the stock-flow (SF) problem, which refers to the difficulty of inferring the behavior of a stock variable given information regarding its inflows and outflows. We elaborated on the idea that global thinking is beneficial for comprehending SF problems and proposed that global thinking enhancing display based on highlighting the areas of difference could be a possible way to shift one's thinking process to the right one, which was proved by two studies. Theoretical and practical implications are discussed.
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Affiliation(s)
- Han Qiao
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Jingyu Zhang
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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González-Parra G, Arenas AJ. Mathematical Modeling of SARS-CoV-2 Omicron Wave under Vaccination Effects. COMPUTATION (BASEL, SWITZERLAND) 2023; 11:36. [PMID: 38957648 PMCID: PMC11218807 DOI: 10.3390/computation11020036] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
Over the course of the COVID-19 pandemic millions of deaths and hospitalizations have been reported. Different SARS-CoV-2 variants of concern have been recognized during this pandemic and some of these variants of concern have caused uncertainty and changes in the dynamics. The Omicron variant has caused a large amount of infected cases in the US and worldwide. The average number of deaths during the Omicron wave toll increased in comparison with previous SARS-CoV-2 waves. We studied the Omicron wave by using a highly nonlinear mathematical model for the COVID-19 pandemic. The novel model includes individuals who are vaccinated and asymptomatic, which influences the dynamics of SARS-CoV-2. Moreover, the model considers the waning of the immunity and efficacy of the vaccine against the Omicron strain. This study uses the facts that the Omicron strain has a higher transmissibility than the previous circulating SARS-CoV-2 strain but is less deadly. Preliminary studies have found that Omicron has a lower case fatality rate compared to previous circulating SARS-CoV-2 strains. The simulation results show that even if the Omicron strain is less deadly it might cause more deaths, hospitalizations and infections. We provide a variety of scenarios that help to obtain insight about the Omicron wave and its consequences. The proposed mathematical model, in conjunction with the simulations, provides an explanation for a large Omicron wave under various conditions related to vaccines and transmissibility. These results provide an awareness that new SARS-CoV-2 variants can cause more deaths even if their fatality rate is lower.
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Affiliation(s)
- Gilberto González-Parra
- Department of Mathematics, New Mexico Tech, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA
| | - Abraham J. Arenas
- Departamento de Matematicas y Estadistica, Universidad de Cordoba, Monteria 230002, Colombia
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Harman JL, Weinhardt JM, Beck JW, Mai I. Interpreting time-series COVID data: reasoning biases, risk perception, and support for public health measures. Sci Rep 2021; 11:15585. [PMID: 34341415 PMCID: PMC8329148 DOI: 10.1038/s41598-021-95134-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/20/2021] [Indexed: 12/16/2022] Open
Abstract
Effective risk communication during the COVID-19 pandemic is critical for encouraging appropriate public health behaviors. One way that the public is informed about COVID-19 numbers is through reports of daily new cases. However, presenting daily cases has the potential to lead to a dynamic reasoning bias that stems from intuitive misunderstandings of accumulation. Previous work in system dynamics shows that even highly educated individuals with training in science and math misunderstand basic concepts of accumulation. In the context of COVID-19, relying on the single cue of daily new cases can lead to relaxed attitudes about the risk of COVID-19 when daily new cases begin to decline. This situation is at the very point when risk is highest because even though daily new cases have declined, the active number of cases are highest because they have been accumulating over time. In an experiment with young adults from the USA and Canada (N = 551), we confirm that individuals fail to understand accumulation regarding COVID-19, have less concern regarding COVID-19, and decrease endorsement for public health measures as new cases decline but when active cases are at the highest point. Moreover, we experimentally manipulate different dynamic data visualizations and show that presenting data highlighting active cases and minimizing new cases led to increased concern and increased endorsement for COVID-19 health measures compared to a control condition highlighting daily cases. These results hold regardless of country, political affiliation, and individual differences in decision making. This study has implications for communicating the risks of contracting COVID-19 and future public health issues.
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Affiliation(s)
- Jason L Harman
- Department of Psychology, Louisiana State University, Baton Rouge, USA.
| | | | - James W Beck
- Department of Psychology, University of Waterloo, Waterloo, Canada
| | - Ivy Mai
- Haskayne School of Business, University of Calgary, Calgary, Canada
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Impact of a New SARS-CoV-2 Variant on the Population: A Mathematical Modeling Approach. MATHEMATICAL AND COMPUTATIONAL APPLICATIONS 2021. [DOI: 10.3390/mca26020025] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Several SARS-CoV-2 variants have emerged around the world, and the appearance of other variants depends on many factors. These new variants might have different characteristics that can affect the transmissibility and death rate. The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020 and in some countries the vaccines will not soon be widely available. For this article, we studied the impact of a new more transmissible SARS-CoV-2 strain on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. We studied different scenarios regarding the transmissibility in order to provide a scientific support for public health policies and bring awareness of potential future situations related to the COVID-19 pandemic. We constructed a compartmental mathematical model based on differential equations to study these different scenarios. In this way, we are able to understand how a new, more infectious strain of the virus can impact the dynamics of the COVID-19 pandemic. We studied several metrics related to the possible outcomes of the COVID-19 pandemic in order to assess the impact of a higher transmissibility of a new SARS-CoV-2 strain on these metrics. We found that, even if the new variant has the same death rate, its high transmissibility can increase the number of infected people, those hospitalized, and deaths. The simulation results show that health institutions need to focus on increasing non-pharmaceutical interventions and the pace of vaccine inoculation since a new variant with higher transmissibility, such as, for example, VOC-202012/01 of lineage B.1.1.7, may cause more devastating outcomes in the population.
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Jalali MS, Botticelli M, Hwang RC, Koh HK, McHugh RK. The opioid crisis: need for systems science research. Health Res Policy Syst 2020; 18:88. [PMID: 32771004 PMCID: PMC7414582 DOI: 10.1186/s12961-020-00598-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 06/29/2020] [Indexed: 01/07/2023] Open
Abstract
The opioid epidemic in the United States has had a devastating impact on millions of people as well as on their families and communities. The increased prevalence of opioid misuse, use disorder and overdose in recent years has highlighted the need for improved public health approaches for reducing the tremendous harms of this illness. In this paper, we explain and call for the need for more systems science approaches, which can uncover the complexities of the opioid crisis, and help evaluate, analyse and forecast the effectiveness of ongoing and new policy interventions. Similar to how a stream of systems science research helped policy development in infectious diseases and obesity, more systems science research is needed in opioids.
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Affiliation(s)
- Mohammad S. Jalali
- grid.38142.3c000000041936754XMGH Institute for Technology Assessment, Harvard Medical School, 101 Merrimac St, Suite 1010, Boston, MA 02114 United States of America ,grid.116068.80000 0001 2341 2786MIT Sloan School of Management, 100 Main St, Cambridge, MA 02142 United States of America
| | - Michael Botticelli
- grid.239424.a0000 0001 2183 6745Grayken Center for Addiction, Boston Medical Center, Boston, MA United States of America
| | - Rachael C. Hwang
- grid.116068.80000 0001 2341 2786MIT Sloan School of Management, 100 Main St, Cambridge, MA 02142 United States of America
| | - Howard K. Koh
- grid.38142.3c000000041936754XT.H. Chan School of Public Health, Harvard
University, Boston, MA United States of America ,grid.38142.3c000000041936754XHarvard Kennedy School, Harvard University, Cambridge, MA United States of America
| | - R. Kathryn McHugh
- grid.38142.3c000000041936754XMGH Institute for Technology Assessment, Harvard Medical School, 101 Merrimac St, Suite 1010, Boston, MA 02114 United States of America ,grid.240206.20000 0000 8795 072XDivision of Alcohol and Drug Abuse, McLean Hospital, Belmont, MA United States of America
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Abstract
This paper describes the Multimedia Application for Diet Management (MADiMan), a system that supports users in managing their diets while admitting diet transgressions. MADiMan consists of a numerical reasoner that takes into account users’ dietary constraints and automatically adapts the users’ diet, and of a natural language generation (NLG) system that automatically creates textual messages for explaining the results provided by the reasoner with the aim of persuading users to stick to a healthy diet. In the first part of the paper, we introduce the MADiMan system and, in particular, the basic mechanisms related to reasoning, data interpretation and content selection for a numeric data-to-text NLG system. We also discuss a number of factors influencing the design of the textual messages produced. In particular, we describe in detail the design of the sentence-aggregation procedure, which determines the compactness of the final message by applying two aggregation strategies. In the second part of the paper, we present the app that we developed, CheckYourMeal!, and the results of two human-based quantitative evaluations of the NLG module conducted using CheckYourMeal! in a simulation. The first evaluation, conducted with twenty users, ascertained both the perceived usefulness of graphics/text and the appeal, easiness and persuasiveness of the textual messages. The second evaluation, conducted with thirty-nine users, ascertained their persuasive power. The evaluations were based on the analysis of questionnaires and of logged data of users’ behaviour. Both evaluations showed significant results.
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Dynamic Performance Management: An Approach for Managing the Common Goods. SUSTAINABILITY 2019. [DOI: 10.3390/su11226435] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Public organizations need innovative approaches for managing common goods and to explain the dynamics linking the (re)generation of common goods and organizational performance. Although system dynamics is recognised as a useful approach for managing common goods, public organizations rarely adopt the system dynamics for this goal. The paper aims to review the literature on the system dynamics and its recent application, known as dynamic performance management, to highlight the state of the art and future opportunities on the management of common goods. The authors analyzed 144 documents using a systematic literature review. The results obtained outline a fair number of documents, countries and journals involving the study of system dynamics, but do not cover sufficient research on the linking between the (re)generation of common goods and organizational performance. This paper outlines academic and practical contributions. Firstly, it contributes to the theory of common goods. It provides insight for linking the management of common goods and organizational performance through the use of dynamic performance management approach. Furthermore, it shows scholars the main research opportunities. Secondly, it indicates to practitioners the documents providing useful ideas on the adoption of system dynamics for managing common goods.
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Jalali MS, Siegel M, Madnick S. Decision-making and biases in cybersecurity capability development: Evidence from a simulation game experiment. JOURNAL OF STRATEGIC INFORMATION SYSTEMS 2019. [DOI: 10.1016/j.jsis.2018.09.003] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Jalali MS, Rahmandad H, Bullock SL, Lee-Kwan SH, Gittelsohn J, Ammerman A. Dynamics of intervention adoption, implementation, and maintenance inside organizations: The case of an obesity prevention initiative. Soc Sci Med 2018; 224:67-76. [PMID: 30763824 DOI: 10.1016/j.socscimed.2018.12.021] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 10/22/2018] [Accepted: 12/15/2018] [Indexed: 12/11/2022]
Abstract
Overall impact of public health prevention interventions relies not only on the average efficacy of an intervention, but also on the successful adoption, implementation, and maintenance (AIM) of that intervention. In this study, we aim to understand the dynamics that regulate AIM of organizational level intervention programs. We focus on two well-documented obesity prevention interventions, implemented in food carry-outs and stores in low-income urban areas of Baltimore, Maryland, which aimed to improve dietary behaviour for adults by providing access to healthier foods and point-of-purchase promotions. Building on data from field observations, in-depth interviews, and data discussed in previous publications, as well as the strategy and organizational behaviour literature, we developed a system dynamics model of the key processes of AIM. With simulation analysis, we show several reinforcing mechanisms that span stakeholder motivation, communications, and implementation quality and costs can turn small changes in the process of AIM into big difference in the overall impact of the intervention. Specifically, small changes in the allocation of resources to communication with stakeholders of intervention could have a nonlinear long-term impact if those additional resources can turn stakeholders into allies of the intervention, reducing the erosion rates and enhancing sustainability. We present how the dynamics surrounding communication, motivation, and erosion can create significant heterogeneity in the overall impact of otherwise similar interventions. Therefore, careful monitoring of how those dynamics unfold, and timely adjustments to keep the intervention on track are critical for successful implementation and maintenance.
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Affiliation(s)
- Mohammad S Jalali
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA; Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Hazhir Rahmandad
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Sally Lawrence Bullock
- Department of Nutrition, Gillings School of Global Public Health, UNC Center for Health Promotion and Disease Prevention (a CDC Prevention Research Center), University of North Carolina at Chapel Hill, NC, USA.
| | - Seung Hee Lee-Kwan
- Department of International Health, Center for Human Nutrition, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Joel Gittelsohn
- Department of International Health, Center for Human Nutrition, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Alice Ammerman
- Department of Nutrition, Gillings School of Global Public Health, UNC Center for Health Promotion and Disease Prevention (a CDC Prevention Research Center), University of North Carolina at Chapel Hill, NC, USA.
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Ghaffarzadegan N, Larson RC. SD Meets OR: A New Synergy to Address Policy Problems. SYSTEM DYNAMICS REVIEW 2018; 34:327-353. [PMID: 32390689 PMCID: PMC7207037 DOI: 10.1002/sdr.1598] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
We reflect on our past seven years of collaboration to develop systems models of U.S. higher education and scientific workforce development. Based on three recent modeling examples, we offer a methodological proposition that many traditional Operations Research (OR) models can be improved by including feedback processes as is commonly done in system dynamics (SD) modeling. Such models, even if simple and approximate, can be powerful, insightful, easy to communicate, and effective. While these modeling examples may not follow conventional SD or OR modeling, they benefit from and contribute to both schools of modeling. We argue that to build such synergy, modeling teams should be willing to create models building on the strengths of each school of modeling.
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Affiliation(s)
- Navid Ghaffarzadegan
- Virginia Tech, Department of Industrial and Systems Engineering
- correspondence to , 703-538-8434
| | - Richard C. Larson
- Massachusetts Institute of Technology, Institute for Data, Systems, and Society
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Dynamics of Implementation and Maintenance of Organizational Health Interventions. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2017; 14:ijerph14080917. [PMID: 28809807 PMCID: PMC5580620 DOI: 10.3390/ijerph14080917] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 07/26/2017] [Accepted: 08/11/2017] [Indexed: 12/22/2022]
Abstract
In this study, we present case studies to explore the dynamics of implementation and maintenance of health interventions. We analyze how specific interventions are built and eroded, how the building and erosion mechanisms are interconnected, and why we can see significantly different erosion rates across otherwise similar organizations. We use multiple comparative obesity prevention case studies to provide empirical information on the mechanisms of interest, and use qualitative systems modeling to integrate our evolving understanding into an internally consistent and transparent theory of the phenomenon. Our preliminary results identify reinforcing feedback mechanisms, including design of organizational processes, motivation of stakeholders, and communication among stakeholders, which influence implementation and maintenance of intervention components. Over time, these feedback mechanisms may drive a wedge between otherwise similar organizations, leading to distinct configurations of implementation and maintenance processes.
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Anselma L, Mazzei A, De Michieli F. An artificial intelligence framework for compensating transgressions and its application to diet management. J Biomed Inform 2017; 68:58-70. [PMID: 28254495 DOI: 10.1016/j.jbi.2017.02.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 02/15/2017] [Accepted: 02/26/2017] [Indexed: 10/20/2022]
Abstract
Today, there is considerable interest in personal healthcare. The pervasiveness of technology allows to precisely track human behavior; however, when dealing with the development of an intelligent assistant exploiting data acquired through such technologies, a critical issue has to be taken into account; namely, that of supporting the user in the event of any transgression with respect to the optimal behavior. In this paper we present a reasoning framework based on Simple Temporal Problems that can be applied to a general class of problems, which we called cake&carrot problems, to support reasoning in presence of human transgression. The reasoning framework offers a number of facilities to ensure a smart management of possible "wrong behaviors" by a user to reach the goals defined by the problem. This paper describes the framework by means of the prototypical use case of diet domain. Indeed, following a healthy diet can be a difficult task for both practical and psychological reasons and dietary transgressions are hard to avoid. Therefore, the framework is tolerant to dietary transgressions and adapts the following meals to facilitate users in recovering from such transgressions. Finally, through a simulation involving a real hospital menu, we show that the framework can effectively achieve good results in a realistic scenario.
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Affiliation(s)
- Luca Anselma
- Dipartimento di Informatica, Università di Torino, Corso Svizzera 185, 10149 Torino, Italy.
| | - Alessandro Mazzei
- Dipartimento di Informatica, Università di Torino, Corso Svizzera 185, 10149 Torino, Italy.
| | - Franco De Michieli
- Dipartimento di Scienze Mediche, Ospedale San Giovanni Battista, Università di Torino, Torino, Italy.
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The Application of Systems Science to Addressing Obesity at the Workplace: Tapping into Unexplored Potential. J Occup Environ Med 2016; 58:123-6. [PMID: 26849255 DOI: 10.1097/jom.0000000000000648] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of the study was to address the need for explicit recognition that obesity is complex in its biological, social, psychological, and societal determinants and ramifications, and that applications of programs to address obesity at the workplace need to recognize this setting as a complex social environment. Efforts to address this complexity more meaningfully demand intentional application of systems science principles and approaches. METHOD Along with several relevant examples, a description of systems sciences and the application of its principles to obesity and the workplace setting are presented. CONCLUSIONS Systems science provides a method to explore large proportions of unexplored potential and unexplained variation in obesity research as applied to the workplace.
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Ghaffarzadegan N, Ebrahimvandi A, Jalali MS. A Dynamic Model of Post-Traumatic Stress Disorder for Military Personnel and Veterans. PLoS One 2016; 11:e0161405. [PMID: 27716776 PMCID: PMC5055362 DOI: 10.1371/journal.pone.0161405] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Accepted: 07/11/2016] [Indexed: 11/19/2022] Open
Abstract
Post-traumatic stress disorder (PTSD) stands out as a major mental illness; however, little is known about effective policies for mitigating the problem. The importance and complexity of PTSD raise critical questions: What are the trends in the population of PTSD patients among military personnel and veterans in the postwar era? What policies can help mitigate PTSD? To address these questions, we developed a system dynamics simulation model of the population of military personnel and veterans affected by PTSD. The model includes both military personnel and veterans in a “system of systems.” This is a novel aspect of our model, since many policies implemented at the military level will potentially influence (and may have side effects on) veterans and the Department of Veterans Affairs. The model is first validated by replicating the historical data on PTSD prevalence among military personnel and veterans from 2000 to 2014 (datasets from the Department of Defense, the Institute of Medicine, the Department of Veterans Affairs, and other sources). The model is then used for health policy analysis. Our results show that, in an optimistic scenario based on the status quo of deployment to intense/combat zones, estimated PTSD prevalence among veterans will be at least 10% during the next decade. The model postulates that during wars, resiliency-related policies are the most effective for decreasing PTSD. In a postwar period, current health policy interventions (e.g., screening and treatment) have marginal effects on mitigating the problem of PTSD, that is, the current screening and treatment policies must be revolutionized to have any noticeable effect. Furthermore, the simulation results show that it takes a long time, on the order of 40 years, to mitigate the psychiatric consequences of a war. Policy and financial implications of the findings are discussed.
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Affiliation(s)
- Navid Ghaffarzadegan
- Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Alireza Ebrahimvandi
- Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Mohammad S. Jalali
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- * E-mail:
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Little JC, Hester ET, Carey CC. Assessing and Enhancing Environmental Sustainability: A Conceptual Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:6830-6845. [PMID: 27152660 DOI: 10.1021/acs.est.6b00298] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
While sustainability is an essential concept to ensure the future of humanity and the integrity of the resources and ecosystems on which we depend, identifying a comprehensive yet realistic way to assess and enhance sustainability may be one of the most difficult challenges of our time. We review the primary environmental sustainability assessment approaches, categorizing them as either being design-based or those that employ computational frameworks and/or indicators. We also briefly review approaches used for assessing economic and social sustainability because sustainability necessitates integrating environmental, economic, and social elements. We identify the collective limitations of the existing assessment approaches, showing that there is not a consistent definition of sustainability, that the approaches are generally not comprehensive and are subject to unintended consequences, that there is little to no connection between bottom-up and top-down approaches, and that the field of sustainability is largely fragmented, with a range of academic disciplines and professional organizations pursuing similar goals, but without much formal coordination. We conclude by emphasizing the need for a comprehensive definition of sustainability (that integrates environmental, economic, and social aspects) with a unified system-of-systems approach that is causal, modular, tiered, and scalable, as well as new educational and organizational structures to improve systems-level interdisciplinary integration.
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Affiliation(s)
- John C Little
- Department of Civil and Environmental Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States
| | - Erich T Hester
- Department of Civil and Environmental Engineering, Virginia Tech , Blacksburg, Virginia 24061, United States
| | - Cayelan C Carey
- Department of Biological Sciences, Virginia Tech , Blacksburg, Virginia 24061, United States
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