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Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province
BACKGROUND: Health impact assessment (HIA) is a procedure, method and tool for evaluating the potential health impacts of policies, plans and construction projects, as well as the distribution of these impacts on population. Majority of international studies on health impact assessment have focussed...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626660/ https://www.ncbi.nlm.nih.gov/pubmed/37932791 http://dx.doi.org/10.1186/s12961-023-01064-9 |
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author | Liu, Xiang Liu, Yingzi Xu, Yanyun Song, Liyuan Huang, Ziyue Zhu, Xingyu Zhang, Meng |
author_facet | Liu, Xiang Liu, Yingzi Xu, Yanyun Song, Liyuan Huang, Ziyue Zhu, Xingyu Zhang, Meng |
author_sort | Liu, Xiang |
collection | PubMed |
description | BACKGROUND: Health impact assessment (HIA) is a procedure, method and tool for evaluating the potential health impacts of policies, plans and construction projects, as well as the distribution of these impacts on population. Majority of international studies on health impact assessment have focussed on conceptual papers or case evaluations, neglecting participants’ views on policies. METHODS: A semi-structured interview with 30 health impact assessment experts was employed in this study, and the Nvivo software was utilized to analyse factors that influence policy identification. Subsequently, a multi-stage stratified random sampling method was adopted to survey 655 pilot staff members involved in health impact assessment in Zhejiang Province. Descriptive statistics were used to describe the current status and identify the factors influencing policy identification. In addition, hierarchical linear regression analysis and structural equation modelling were employed to determine the relationship between policy identification and influencing factors. RESULTS: Statistically significant differences were found among participants in the level of identification of policies across three dimensions. The policy sentiment dimension had the highest score (4.137 ± 0.664), followed by policy cognition (4.075 ± 0.632) and policy evaluation (3.631 ± 0.797) dimensions. Subject trust had a positive impact on policy cognition (β = 0.503, P < 0.001), policy sentiment (β = 0.504, P < 0.001) and policy evaluation (β = 0.465, P < 0.001). Procedural justice had a positive impact on policy sentiment (β = 0.085, P < 0.01) and policy evaluation (β = 0.084, P < 0.05), but not policy cognition (β = 0.056, P > 0.05). Policy identification is influenced by age and average monthly salary among other factors. CONCLUSION: These results highlight the importance of subjective trust and procedural justice in policy identification of health impact assessment. They provide valuable insights to developing interventions to overcome barriers to the implementation and enhancement of global identification of policies. Going forward, cross-sectoral synergies, enhanced international communication and training to increase participants’ trust in the policy should be optimized to improve health impact assessment. Additional measures should be taken, such as ensuring seamless communication channels, embedding health impact assessment in administrative mechanisms, and establishing strong oversight and grievance mechanisms to improve fairness and transparency in the implementation and results of health impact assessment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12961-023-01064-9. |
format | Online Article Text |
id | pubmed-10626660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106266602023-11-07 Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province Liu, Xiang Liu, Yingzi Xu, Yanyun Song, Liyuan Huang, Ziyue Zhu, Xingyu Zhang, Meng Health Res Policy Syst Research BACKGROUND: Health impact assessment (HIA) is a procedure, method and tool for evaluating the potential health impacts of policies, plans and construction projects, as well as the distribution of these impacts on population. Majority of international studies on health impact assessment have focussed on conceptual papers or case evaluations, neglecting participants’ views on policies. METHODS: A semi-structured interview with 30 health impact assessment experts was employed in this study, and the Nvivo software was utilized to analyse factors that influence policy identification. Subsequently, a multi-stage stratified random sampling method was adopted to survey 655 pilot staff members involved in health impact assessment in Zhejiang Province. Descriptive statistics were used to describe the current status and identify the factors influencing policy identification. In addition, hierarchical linear regression analysis and structural equation modelling were employed to determine the relationship between policy identification and influencing factors. RESULTS: Statistically significant differences were found among participants in the level of identification of policies across three dimensions. The policy sentiment dimension had the highest score (4.137 ± 0.664), followed by policy cognition (4.075 ± 0.632) and policy evaluation (3.631 ± 0.797) dimensions. Subject trust had a positive impact on policy cognition (β = 0.503, P < 0.001), policy sentiment (β = 0.504, P < 0.001) and policy evaluation (β = 0.465, P < 0.001). Procedural justice had a positive impact on policy sentiment (β = 0.085, P < 0.01) and policy evaluation (β = 0.084, P < 0.05), but not policy cognition (β = 0.056, P > 0.05). Policy identification is influenced by age and average monthly salary among other factors. CONCLUSION: These results highlight the importance of subjective trust and procedural justice in policy identification of health impact assessment. They provide valuable insights to developing interventions to overcome barriers to the implementation and enhancement of global identification of policies. Going forward, cross-sectoral synergies, enhanced international communication and training to increase participants’ trust in the policy should be optimized to improve health impact assessment. Additional measures should be taken, such as ensuring seamless communication channels, embedding health impact assessment in administrative mechanisms, and establishing strong oversight and grievance mechanisms to improve fairness and transparency in the implementation and results of health impact assessment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12961-023-01064-9. BioMed Central 2023-11-06 /pmc/articles/PMC10626660/ /pubmed/37932791 http://dx.doi.org/10.1186/s12961-023-01064-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Liu, Xiang Liu, Yingzi Xu, Yanyun Song, Liyuan Huang, Ziyue Zhu, Xingyu Zhang, Meng Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province |
title | Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province |
title_full | Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province |
title_fullStr | Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province |
title_full_unstemmed | Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province |
title_short | Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province |
title_sort | current status and influencing factors of policy identification in health impact assessment: a case study of zhejiang province |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626660/ https://www.ncbi.nlm.nih.gov/pubmed/37932791 http://dx.doi.org/10.1186/s12961-023-01064-9 |
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