Unsettling Care Infrastructures: From the Individual to the Structural in a Digital Maternal and Child Health Intervention
Authors
Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Mental Health Apps & Online Support CommunitiesDeveloping Countries & HCI for Development (HCI4D)Physicians, Nurses & CliniciansCommunity Health WorkersSocial Workers
Title of the Paper
Unsettling Care Infrastructures: From the Individual to the Structural in a Digital Maternal and Child Health Intervention
Paper Information
- Subject Area: Digital healthcare and care technologies, with a focus on maternal and child health (MCH) and related information services in the context of developing countries.
- Keywords: Care, future of labor, maternal and child health, chat platforms, India, structural inequality, women's health, digital health services, health infrastructure, behavior change
Research Background and Issues
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What problems or challenges did the authors identify?
- Maternal and child health (MCH) behavior change interventions in developing countries are predominantly individual-centric, lacking responses to broader structural issues such as resource scarcity, overburdened care labor, and gendered social dynamics.
- Existing digital health services (e.g., chat platforms) can disseminate health information but fail to adequately address barriers faced by women and families in navigating healthcare systems, accessing emotional support, and achieving equitable access to health services.
- Healthcare workers are often overlooked in technology-supported health interventions.
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Why is this issue important?
- While digital interventions in the MCH field are widely promoted, their sustainability and social impact may be limited if broader structural issues are not addressed.
- In the context of developing countries, fragmented and inequitable health systems constrain the effectiveness of technological interventions and exacerbate the burden of paid and unpaid care work, predominantly borne by women.
- There is currently a lack of research from the perspective of the political economy of gender and labor.
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Research Motivation and Related Work
- The research was motivated by the widespread deployment of WhatsApp health information services, which have become one of the only large-scale digital health interventions in the MCH domain.
- The authors were inspired by research on the politics of care and gender, as well as academic discussions on how care work develops under the global forces of capitalism, colonialism, and patriarchy.
- The study complements previous research on individual behavior change interventions (e.g., data accessibility, health outcomes) by focusing on the social structural implications of large-scale health interventions.
Solutions
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What methods or solutions did the authors propose?
- Conducted a comprehensive qualitative study of a digital maternal and child health intervention implemented across eight states in India. The project included hospital-based patient education programs and WhatsApp-based health information services.
- Leveraged the theory of "unsettling care" to explore the roles and limitations of these interventions within inequitable healthcare systems, particularly their structural impacts.
- Collected multi-faceted data through interviews and observations to study the perspectives of various stakeholders, including NGO staff, healthcare workers, and families using the services.
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What are the innovative aspects of this solution?
- Proposed that digital health services should go beyond individual behavior change to address deeper social structural issues.
- Reoriented the design of healthcare services from a political economy and gender perspective, emphasizing the role of humans in technology rather than focusing solely on automation and scalability.
- Highlighted the importance of transforming information services into tools that support health rights rather than merely disseminating knowledge.
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What are the implementation steps and key technologies used?
- Analyzed usage data from WhatsApp information services, collecting approximately 13,200 user queries and 45 family conversation samples.
- Observed the implementation of hospital-based care education programs and studied the workflows of healthcare workers managing WhatsApp services to understand work demands and challenges.
- Conducted interviews to gain in-depth insights into the motivations, perceptions, and experiences of different stakeholders.
Research Outcomes
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What specific outcomes were achieved?
- Redefined the value of care work: The intervention successfully enhanced families' access to education by elevating the status and working conditions of care workers.
- WhatsApp information services went beyond behavior change, becoming a critical tool for families to navigate opaque healthcare systems, providing emotional support, navigation assistance, and basic medical advice.
- Revealed how digital health interventions can form unexpected networks of labor management and technology-human resource collaboration.
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What advantages does it have compared to existing solutions?
- Reexamined the design and implementation of digital health services from the perspective of gendered labor division and social structural inequality, rather than merely quantifying the effects of behavior change.
- Developed targeted strategies to enhance families' decision-making capabilities within complex healthcare systems through medical knowledge, while supporting patients in advocating for their health rights.
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What were the experimental or evaluation results?
- The study identified the main types of user interactions on the WhatsApp platform (e.g., neonatal care, nutrition, symptom management).
- Medical Support Executives (MSEs) successfully built trust with service users through supportive conversations and phone calls.
- Data indicated that despite service limitations, users were willing to explore its scope and benefited from information navigation.
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Limitations and Future Directions
- Limitations:
- The sample size of the study was limited, insufficient to represent the diverse experiences across different regions and cultural contexts.
- The perspectives of potential users who did not utilize the services were not covered.
- Future Directions:
- Design information services that explicitly support patient rights to further reduce social inequities.
- Investigate how private intervention programs (e.g., NGO-led services) can be effectively integrated into public health systems to ensure sustainability and scalability.
- Continue to focus on enhancing the status of care labor within inequitable structures, supporting labor rights, and ensuring comfortable working conditions.
- Limitations:
Research Questions / Practical Problems
Question signals indexed for this paper.
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Research Questions
3- How can digital maternal and infant health interventions expand from individual behavior change to addressing structural problems (e.g., resource scarcity and gender discrimination)?Category: Healthcare Equity, Clinical Algorithm Fairness, and Marginalized Patient SupportSimilar questionsarrow_forward
- How do existing digital health services (e.g., WhatsApp health information platforms) affect users' health decisions in unequal healthcare environments?Category: Healthcare Equity, Clinical Algorithm Fairness, and Marginalized Patient SupportSimilar questionsarrow_forward
- How can digital health interventions improve the status and working conditions of care workers?Category: Healthcare Equity, Clinical Algorithm Fairness, and Marginalized Patient SupportSimilar questionsarrow_forward
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Practical Problems
1- Women struggle to independently access equitable healthcare, and care workers are neglected.Category: Healthcare Equity, Clinical Algorithm Fairness, and Marginalized Patient SupportSimilar questionsarrow_forward
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DOI: https://doi.org/10.1145/3544548.3581553
At a Glance
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Source
CHI
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Year
2023
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Authors
4 authors
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Subtopics
Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia), Mental Health Apps & Online Support Communities, Developing Countries & HCI for Development (HCI4D)
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Professions
Physicians, Nurses & Clinicians, Community Health Workers, Social Workers
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