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Heneghan J, John DC, Bartsch SM, Piltch-Loeb R, Gilbert C, Kass D, Chin KL, Dibbs A, Shah TD, O'Shea KJ, Scannell SA, Martinez MF, Lee BY. A Systems Map of the Challenges of Climate Communication. JOURNAL OF HEALTH COMMUNICATION 2024; 29:77-88. [PMID: 38845202 PMCID: PMC11414781 DOI: 10.1080/10810730.2024.2361842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Over the past sixty years, scientists have been warning about climate change and its impacts on human health, but evidence suggests that many may not be heeding these concerns. This raises the question of whether new communication approaches are needed to overcome the unique challenges of communicating what people can do to slow or reverse climate change. To better elucidate the challenges of communicating about the links between human activity, climate change and its effects, and identify potential solutions, we developed a systems map of the factors and processes involved based on systems mapping sessions with climate change and communication experts. The systems map revealed 27 communication challenges such as "Limited information on how individual actions contribute to collective human activity," "Limited information on how present activity leads to long-term effects," and "Difficult to represent and communicate complex relationships." The systems map also revealed several themes among the identified challenges that exist in communicating about climate change, including a lack of available data and integrated databases, climate change disciplines working in silos, a need for a lexicon that is easily understood by the public, and the need for new communication strategies to describe processes that take time to manifest.
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Affiliation(s)
- Jessie Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Danielle C John
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Pandemic Response Institute, New York City, New York, USA
| | - Sarah M Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Rachael Piltch-Loeb
- Environmental, Occupational, and Geospatial Health Sciences, City University of New York Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Christine Gilbert
- School of Communication & Journalism, Stony Brook University, Stony Brook, New York, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, New York, USA
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Dan Kass
- Vital Strategies, New York, New York, USA
| | - Kevin L Chin
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Alexis Dibbs
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Tej D Shah
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Kelly J O'Shea
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Sheryl A Scannell
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Marie F Martinez
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
| | - Bruce Y Lee
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, USA
- Pandemic Response Institute, New York City, New York, USA
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Maeda H, Tomomatsu I, Iikura I, Ikari M, Kondo Y, Yamamoto M, Tamura M. The care burden for technology-dependent children with long-term home ventilation increases along with the improvement of their motor functions. Eur J Pediatr 2024; 183:135-147. [PMID: 37843613 PMCID: PMC10858118 DOI: 10.1007/s00431-023-05249-w] [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] [Received: 07/14/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/17/2023]
Abstract
Since the establishment of Japan's publicly supported pediatric home medical care (PHMC) system in 2012, the number of technology-dependent children (TDC) who are supported by PHMC has been increasing. We expected care to become easier as TDC mobility increased. However, many family caregivers complained of the opposite, that the burden of care increased as TDC's mobility increased. Therefore, we aimed to study the problems of the care burden of families in relation to the improvement of mobility of TDC with a focus on respiratory support. We conducted a survey among caregivers of TDC in two parts: a first survey was done between 2018 and 2020, and a follow-up survey in 2023. In each medical procedure, the correlation of TDC's motor function level with care burden was analyzed by using correlation analysis. In 15 households, caregivers' activities were monitored to elucidate the problems of the care objectively. The second survey was conducted in February 2023 in TDC whose medical records were available. Analysis of 418 cases showed that care-burden increased with improvements in the children's motor ability in tracheostomy, or remained the same in other procedures. A follow-up study in 262/418 cases of this group showed that part of these TDC with high mobility aged 1-8, after passing through the mobile phase with increased burden of care, had a high potential to be weaned from medical devices. Conclusion: For TDC who acquire motor skills during PHMC, the burden of care for caregivers either increases or remains the same. It is important to maintain social support for TDC on the recovering mobile stage. What is Known: • There was no clear information on the care burden when TDC become mobile. What is New: • We did a qualitative study to show that the care burden increases when TDC become mobile. • In addition, mobike TDC showed a high potential for recovery.
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Affiliation(s)
- Hirotoshi Maeda
- Medical Incorporated Foundation Harutaka Kai, Ueno Tosei Bldg. 9F, Higashi-Ueno 4-23-7, Taito-ku, Tokyo, 110-0015, Japan.
| | - Ikuko Tomomatsu
- TOMO Lab LLC, Shibuya-ku, Tokyo, Japan
- Graduate School of Human Sciences, Osaka University, Suita-city, Osaka, Japan
| | - Izumi Iikura
- Medical Incorporated Foundation Harutaka Kai, Ueno Tosei Bldg. 9F, Higashi-Ueno 4-23-7, Taito-ku, Tokyo, 110-0015, Japan
| | - Masahiro Ikari
- Medical Incorporated Foundation Harutaka Kai, Ueno Tosei Bldg. 9F, Higashi-Ueno 4-23-7, Taito-ku, Tokyo, 110-0015, Japan
| | - Youichi Kondo
- Medical Incorporated Foundation Harutaka Kai, Ueno Tosei Bldg. 9F, Higashi-Ueno 4-23-7, Taito-ku, Tokyo, 110-0015, Japan
| | - Miyuki Yamamoto
- Medical Incorporated Foundation Harutaka Kai, Ueno Tosei Bldg. 9F, Higashi-Ueno 4-23-7, Taito-ku, Tokyo, 110-0015, Japan
- Institude of Human Sciences, University of Tsukuba, Tsukuba-city, Ibaraki, Japan
| | - Masanori Tamura
- Faculty of Medicine, Saitama Medical University, Saitama-city, Saitama, Japan
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Monroy Tapiador MÁ, Climent Alcalá FJ, Rodríguez Alonso A, Molina Amores C, Mellado Peña MJ, Calvo Rey C. [Current situation of children with medical complexity: An experience between primary and hospital care]. Aten Primaria 2021; 53:102046. [PMID: 33873126 PMCID: PMC8079965 DOI: 10.1016/j.aprim.2021.102046] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 12/14/2020] [Accepted: 12/20/2020] [Indexed: 12/05/2022] Open
Abstract
Objetivo Analizar la valoración de la atención a los niños con patología crónica compleja (NPCC) en atención primaria (AP), desde el punto de vista de sus médicos y de sus familias. Diseño Estudio observacional, descriptivo y transversal. Emplazamiento Pediatría de AP y unidad de patología crónica compleja (UPCC) del Hospital Universitario La Paz (HULP). Participantes Pacientes y familiares de la UPCC y sus médicos de AP de la Comunidad de Madrid (CAM). Intervenciones Realización de encuestas validadas presenciales y online. Mediciones principales Grado de satisfacción en la formación, capacitación y manejo específico del NPCC según escalas tipo Likert. Resultados Se encuestaron 53 familias y 170 médicos de AP (96,5% pediatras). Los resultados de la encuesta a familiares revelan descoordinación entre niveles asistenciales (73,6%), escasa confianza en el primer nivel asistencial e impresión de poca capacidad de resolución de problemas por parte de pediatría de AP (50%). Entre los médicos de AP destaca la poca formación para el seguimiento de los NPCC (96,5%), escasa experiencia en su manejo (93%) e insuficiente comunicación con el hospital (80,5%). La falta de tiempo en las consultas es un problema común, percibido por pediatras y pacientes. Conclusiones La falta de coordinación entre AP y atención hospitalaria (AH) se detecta como un problema importante en la continuidad asistencial de NPCC. Son necesarias intervenciones que mejoren esta coordinación. La AP es cercana a la familia, pero precisa mejorar la formación y capacitación de los profesionales en problemas de salud y soporte tecnificado de NPCC, así como incrementar el tiempo necesario para su atención.
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Affiliation(s)
| | - Francisco José Climent Alcalá
- Unidad de Patología Compleja, Servicio de Pediatría Hospitalaria, Enfermedades Infecciosas y Tropicales, Hospital Universitario Infantil La Paz, Madrid, España.
| | - Aroa Rodríguez Alonso
- Unidad de Patología Compleja, Servicio de Pediatría Hospitalaria, Enfermedades Infecciosas y Tropicales, Hospital Universitario Infantil La Paz, Madrid, España
| | - Clara Molina Amores
- Unidad de Patología Compleja, Servicio de Pediatría Hospitalaria, Enfermedades Infecciosas y Tropicales, Hospital Universitario Infantil La Paz, Madrid, España
| | - María José Mellado Peña
- Unidad de Patología Compleja, Servicio de Pediatría Hospitalaria, Enfermedades Infecciosas y Tropicales, Hospital Universitario Infantil La Paz, Madrid, España
| | - Cristina Calvo Rey
- Unidad de Patología Compleja, Servicio de Pediatría Hospitalaria, Enfermedades Infecciosas y Tropicales, Hospital Universitario Infantil La Paz, Madrid, España
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Melluso N, Bonaccorsi A, Chiarello F, Fantoni G. Rapid detection of fast innovation under the pressure of COVID-19. PLoS One 2020; 15:e0244175. [PMID: 33382727 PMCID: PMC7774967 DOI: 10.1371/journal.pone.0244175] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Accepted: 12/04/2020] [Indexed: 01/25/2023] Open
Abstract
Covid-19 has rapidly redefined the agenda of technological research and development both for academics and practitioners. If the medical scientific publication system has promptly reacted to this new situation, other domains, particularly in new technologies, struggle to map what is happening in their contexts. The pandemic has created the need for a rapid detection of technological convergence phenomena, but at the same time it has made clear that this task is impossible on the basis of traditional patent and publication indicators. This paper presents a novel methodology to perform a rapid detection of the fast technological convergence phenomenon that is occurring under the pressure of the Covid-19 pandemic. The fast detection has been performed thanks to the use of a novel source: the online blogging platform Medium. We demonstrate that the hybrid structure of this social journalism platform allows a rapid detection of innovation phenomena, unlike other traditional sources. The technological convergence phenomenon has been modelled through a network-based approach, analysing the differences of networks computed during two time periods (pre and post COVID-19). The results led us to discuss the repurposing of technologies regarding "Remote Control", "Remote Working", "Health" and "Remote Learning".
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Affiliation(s)
- Nicola Melluso
- Department of Energy, Systems, Territory and Construction Engineering, School of Engineering, University of Pisa, Pisa, Italy
| | - Andrea Bonaccorsi
- Department of Energy, Systems, Territory and Construction Engineering, School of Engineering, University of Pisa, Pisa, Italy
| | - Filippo Chiarello
- Department of Energy, Systems, Territory and Construction Engineering, School of Engineering, University of Pisa, Pisa, Italy
| | - Gualtiero Fantoni
- Department of Civil and Industrial Engineering, School of Engineering, University of Pisa, Pisa, Italy
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