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Exploring Influential Factors with Structural Equation Modeling–Artificial Neural Network to Involve Medicine Users in Home Medicine Waste Management and Preventing Pharmacopollution

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  • Wesley Douglas Oliveira Silva

    (Escola UNICAP ICAM-TECH, Universidade Católica de Pernambuco (UNICAP), Recife 50050-900, Brazil
    Management Engineering Department, Universidade Federal de Pernambuco (UFPE), Recife 50740-550, Brazil)

  • Danielle Costa Morais

    (Management Engineering Department, Universidade Federal de Pernambuco (UFPE), Recife 50740-550, Brazil)

  • Ketylen Gomes da Silva

    (Escola UNICAP ICAM-TECH, Universidade Católica de Pernambuco (UNICAP), Recife 50050-900, Brazil)

  • Pedro Carmona Marques

    (EIGeS, Faculty of Engineering, Lusófona University, 1749-024 Lisbon, Portugal
    Instituto Superior de Engenharia de Lisboa (ISEL), Instituto Politécnico de Lisboa, 1959-007 Lisbon, Portugal)

Abstract

The appropriate management of home medical waste is of paramount importance due to the adverse consequences that arise from improper handling. Incorrect disposal practices can lead to pharmacopollution, which poses significant risks to environmental integrity and human well-being. Involving medicine users in waste management empowers them to take responsibility for their waste and make informed decisions to safeguard the environment and public health. The objective of this research was to contribute to the prevention of pharmacopollution by identifying influential factors that promote responsible disposal practices among medicine users. Factors such as attitude, marketing campaigns, collection points, safe handling, medical prescription, package contents, and public policies and laws were examined. To analyze the complex relationships and interactions among these factors, a dual-staged approach was employed, utilizing advanced statistical modeling techniques and deep learning artificial neural network algorithms. Data were collected from 952 respondents in Pernambuco, a state in northeastern Brazil known for high rates of pharmacopollution resulting from improper disposal of household medical waste. The results of the study indicated that the propositions related to safety in handling and medical prescription were statistically rejected in the structural equation modeling (SEM) model. However, in the artificial neural network (ANN) model, these two propositions were found to be important predictors of cooperative behavior, highlighting the ANN’s ability to capture complex, non-linear relationships between variables. The findings emphasize the significance of user cooperation and provide insights for the development of effective strategies and policies to address pharmacopollution.

Suggested Citation

  • Wesley Douglas Oliveira Silva & Danielle Costa Morais & Ketylen Gomes da Silva & Pedro Carmona Marques, 2023. "Exploring Influential Factors with Structural Equation Modeling–Artificial Neural Network to Involve Medicine Users in Home Medicine Waste Management and Preventing Pharmacopollution," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:10898-:d:1191816
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    References listed on IDEAS

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    1. Yumei Luo & Kai Reimers & Lei Yang & Jinping Lin, 2021. "Household Drug Management Practices of Residents in a Second-Tier City in China: Opportunities for Reducing Drug Waste and Environmental Pollution," IJERPH, MDPI, vol. 18(16), pages 1-15, August.
    2. David Carassus & Christophe Favoreu & Damien Gardey, 2014. "Factors that Determine or Influence Managerial Innovation in Public Contexts: The Case of Local Performance Management," Public Organization Review, Springer, vol. 14(2), pages 245-266, June.
    3. Jun Lv & Xuan Liu & Sivhuang Lay, 2021. "The Impact of Consequences Awareness of Public Environment on Medicine Return Behavior: A Moderated Chain Mediation Model," IJERPH, MDPI, vol. 18(18), pages 1-19, September.
    4. Simone Aquino & Glauco Antonio Spina & Maria Antonietta Leitão Zajac & Evandro Luiz Lopes, 2018. "Reverse Logistics of Postconsumer Medicines: The Roles and Knowledge of Pharmacists in the Municipality of São Paulo, Brazil," Sustainability, MDPI, vol. 10(11), pages 1-17, November.
    5. David Carassus & Christophe Favoreu & Damien Gardey, 2014. "Factors That Determine or Influence Managerial Innovation in Public Contexts: The Case of Local Performance Management," Post-Print hal-02431110, HAL.
    6. de Oña, Juan & de Oña, Rocío & Eboli, Laura & Mazzulla, Gabriella, 2013. "Perceived service quality in bus transit service: A structural equation approach," Transport Policy, Elsevier, vol. 29(C), pages 219-226.
    7. Changjoon Lee & Soyoun Lim & Byoungchun Ha, 2021. "Green Supply Chain Management and Its Impact on Consumer Purchase Decision as a Marketing Strategy: Applying the Theory of Planned Behavior," Sustainability, MDPI, vol. 13(19), pages 1-16, October.
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