Sustainable development goals: conceptualization, communication and achievement synergies in a complex network framework

Bellantuono, Loredana; Monaco, A.; Amoroso, Nicola; Aquaro, Vincenzo; Lombardi, Angela; Tangaro, Sabina; Bellotti, Roberto

doi:10.1007/s41109-022-00455-1

Cited by 17 publications

(16 citation statements)

References 45 publications

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“…The sustainable development goals are a set of 17 global goals set by the United Nations in 2015 and recently adopted in the 2030 agenda ( 1–5 ). The goals provide a “shared blueprint for peace and prosperity for people and the planet, now and into the future.” The goals cover a wide range of issues, including poverty, hunger, health, education, climate change, gender equality, water, sanitation, energy, the environment, and social justice ( 5 , 6 ).…”

Section: Introductionmentioning

confidence: 99%

Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries

Piya,

Lennerz

2023

Front. Med.

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Digital Pathology (DP) and Artificial Intelligence (AI) can be useful in low- and middle-income countries; however, many challenges exist. The United Nations developed sustainable development goals that aim to overcome some of these challenges. The sustainable development goals have not been applied to DP/AI applications in low- to middle income countries. We established a framework to align the 17 sustainable development goals with a 27-indicator list for low- and middle-income countries (World Bank/WHO) and a list of 21 essential elements for DP/AI. After categorization into three domains (human factors, IT/electronics, and materials + reagents), we permutated these layers into 153 concatenated statements for prioritization on a four-tiered scale. The two authors tested the subjective ranking framework and endpoints included ranked sum scores and visualization across the three layers. The authors assigned 364 points with 1.1–1.3 points per statement. We noted the prioritization of human factors (43%) at the indicator layer whereas IT/electronic (36%) and human factors (35%) scored highest at the essential elements layer. The authors considered goal 9 (industry, innovation, and infrastructure; average points 2.33; sum 42), goal 4 (quality education; 2.17; 39), and goal 8 (decent work and economic growth; 2.11; 38) most relevant; intra-/inter-rater variability assessment after a 3-month-washout period confirmed these findings. The established framework allows individual stakeholders to capture the relative importance of sustainable development goals for overcoming limitations to a specific problem. The framework can be used to raise awareness and help identify synergies between large-scale global objectives and solutions in resource-limited settings.

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Section: Introductionmentioning

confidence: 99%

Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries

Piya,

Lennerz

2023

Front. Med.

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“…Two main research gaps must be filled to efficiently use OSNs for sustainability awareness and advance the state-of-the-art in this body of knowledge. First, in the literature, scholars have explored how different factors, tools and approaches affect the success of sustainability awareness through OSNs (Chou and Huang, 2021;Sysoieva and Osadcha, 2020); proposed new methods, theoretical frameworks and approaches (Vasseur et al, 2022;Al-Marghilani, 2022); and showed different case examples (Bellantuono et al, 2022;Hurajova et al, 2022). The contributions of these studies should be considered in designing and developing OSNs and sustainability initiatives using OSNs.…”

Section: Introductionmentioning

confidence: 99%

“…First, in the literature, scholars have explored how different factors, tools and approaches affect the success of sustainability awareness through OSNs (Chou and Huang, 2021; Sysoieva and Osadcha, 2020); proposed new methods, theoretical frameworks and approaches (Vasseur et al. , 2022; Al-Marghilani, 2022); and showed different case examples (Bellantuono et al. , 2022; Hurajova et al.…”

Section: Introductionmentioning

confidence: 99%

Framework for using online social networks for sustainability awareness

Chalmeta,

Barbeito-Caamaño

2023

OIR

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Purpose This study aims to contribute to the field of computer systems for sustainability research. It proposes a framework for sustainability awareness using online social networks (OSNs) by analyzing major research streams of the current state of knowledge and different bibliometric variables, and identifies a future research agenda in the field.Design/methodology/approach The preferred reporting items for systematic review and meta-analysis (PRISMA) methodology, content analysis and bibliometric tools were employed to identify, select, collect, synthesize, analyze and evaluate all research published on sustainability awareness using OSNs to provide complete insight into this research area.Findings This study proposed a framework comprising four categories for sustainability awareness using OSNs. These four categories are: the key factors to success, analysis of existing tools, proposal of new methods, approaches and theoretical frameworks, and case examples. In addition, this study synthesized the future research challenges for each category of the proposed framework.Originality/valueFostering sustainability awareness and sustainable behavior using OSNs is a growing area of research that seeks cultural change in society to achieve sustainable development. Through OSNs, people can discover and become aware of the consequences of unsustainable practices and habits in society, and learn how to develop sustainable behavior.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/OIR

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“…To increase the robustness of our analysis, we will employ the tool of complex networks (Newman, 2018 ), that is increasingly used, also in its recent formal developments (Bianconi, 2018 ; Amoroso et al, 2020 , 2021b ), along with or in replacement of traditional statistical techniques to unveil hidden information in many sectors of science and society, such as neuroscience (Sporns, 2011 ; Amoroso et al, 2018 , 2019 ; Bellantuono et al, 2021 ), genetics (Monaco et al, 2019 , 2020 ), economics (Hidalgo et al, 2007 ; Battiston et al, 2012 ; Tacchella et al, 2012 ; Hausmann et al, 2014 ; Bardoscia et al, 2017 , 2021 ; Pugliese et al, 2019 ; Amoroso et al, 2021a ), human mobility (Alessandretti et al, 2018 ), social and development-related issues (Bellantuono et al, 2020 , 2022a , b ).…”

Section: Introductionmentioning

confidence: 99%

Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis

Bellantuono¹,

Monaco²,

Amoroso³

et al. 2022

Front. Big Data

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IntroductionDementia is an umbrella term indicating a group of diseases that affect the cognitive sphere. Dementia is not a mere individual health issue, since its interference with the ability to carry out daily activities entails a series of collateral problems, comprising exclusion of patients from civil rights and welfare, unpaid caregiving work, mostly performed by women, and an additional burden on the public healthcare systems. Thus, gender and wealth inequalities (both among individuals and among countries) tend to amplify the social impact of such a disease. Since at present there is no cure for dementia but only drug treatments to slow down its progress and mitigate the symptoms, it is essential to work on prevention and early diagnosis, identifying the risk factors that increase the probability of its onset. The complex and multifactorial etiology of dementia, resulting from an interplay between genetics and environmental factors, can benefit from a multidisciplinary approach that follows the “One Health” guidelines of the World Health Organization.MethodsIn this work, we apply methods of Artificial Intelligence and complex systems physics to investigate the possibility to predict dementia prevalence throughout world countries from a set of variables concerning individual health, food consumption, substance use and abuse, healthcare system efficiency. The analysis uses publicly available indicator values at a country level, referred to a time window of 26 years.ResultsEmploying methods based on eXplainable Artificial Intelligence (XAI) and complex networks, we identify a group of lifestyle factors, mostly concerning nutrition, that contribute the most to dementia incidence prediction.DiscussionThe proposed approach provides a methodological basis to develop quantitative tools for action patterns against such a disease, which involves issues deeply related with sustainable, such as good health and resposible food consumption.

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Sustainable development goals: conceptualization, communication and achievement synergies in a complex network framework

Cited by 17 publications

References 45 publications

Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries

Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries

Framework for using online social networks for sustainability awareness

Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis

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