Bridging Generations in Long Term Care Workforce and Family Care Decisions (2026-2027)

Please note that this is a joint Duke-DKU team that will include faculty and students from both institutions. Applicants should be excited to work collaboratively across institutions and should expect to coordinate meetings across time zones.

Background

Populations worldwide are aging at an unprecedented pace, generating growing demand for long-term care (LTC) systems that enable older adults to live with dignity, independence and quality of life. Yet evidence from international organizations such as the World Health Organization (WHO) and the Organization for Economic Co-operation and Development (OECD) consistently shows that LTC systems, especially the care workforce, remain underdeveloped and under-resourced. Across many contexts, both formal care workers (e.g., nurses, trained aides) and informal caregivers (e.g., family members, domestic helpers, migrant workers) operate within fragmented systems characterized by workforce shortages, uneven training standards, low social recognition and limited policy support.

While formal LTC workforce shortages are well documented, informal caregivers continue to shoulder a substantial share of day-to-day care responsibilities, often with little training, regulation or institutional backing. At the same time, rapid social and demographic change is reshaping how different generations perceive aging, family responsibility and care work. Shifts in economic conditions, gender norms and career aspirations influence both people who enter LTC-related roles and how families make decisions about aging and care across the life course. As a result, boundaries between “formal” and “informal” care are increasingly blurred, with individuals moving between care roles, sectors and family responsibilities over time.

These evolving dynamics raise critical questions for research and policy: How are LTC workers trained, supported, and valued across different systems? How do intergenerational attitudes and sociocultural contexts shape participation in care work and perceptions of care quality? How do families and individuals navigate decisions about aging, caregiving arrangements, and workforce engagement? And how can policies better integrate formal and informal care systems to build more equitable, sustainable, and person-centered LTC models across diverse cultural settings?

Project Description

This mixed-method, cross-cultural project will investigate how workforce preparedness, intergenerational values and sociocultural norms shape LTC workforce development and family care decision-making across several countries. The research will be carried out in four phases:

Phase 1 — Background Review and Policy Mapping
Team members will map national and subnational LTC policies in China, the United States and selected comparator countries (such as Singapore, Norway and the U.K.). Analyses will draw on the WHO Decade of Healthy Ageing and Decent Work for Care Workers frameworks. A scoping literature review will examine determinants of workforce engagement and generational differences in attitudes toward aging, family care roles and LTC careers.

Phase 2 — Data Collection and Field Engagement
The team will use secondary international and national datasets (e.g., OECD LTC indicators, WHO Global Health Observatory, China’s National Bureau of Statistics) to identify trends in workforce composition, aging attitudes and care preferences. Complementary surveys will be administered to young adults (ages 18-35) and mid-to-older adults (ages 45-70) to assess perceptions of caregiving roles and job attractiveness. Interviews and focus groups with care workers, older adults and family caregivers will explore motivations, expectations and values across cultural contexts. The team will work with community partners — such as senior centers, NGOs and hospitals in Kunshan, Durham and international sites — to refine tools and support pilot implementation.

Phase 3 — Data Analysis and Comparison
Quantitative data will be analyzed using descriptive and comparative statistics. Qualitative interview and focus group data will be coded thematically using NVivo. Cross-country teams will synthesize findings to identify convergent themes and contrasting patterns. DKU-Duke workshops will support visualization, interpretation and integration of mixed-method evidence.

Phase 4 — Dissemination and Knowledge Translation
Team members will translate findings into policy briefs, infographics, conference presentations and academic manuscripts. Community events and partner webinars at DKU and Duke will share results with stakeholders and support collaborative policy dialogue. IRB approval will be obtained for all human subjects activities.

Anticipated Outputs

Comparative LTC policy and workforce database
Policy briefs and infographics for public and policy audiences
Joint DKU-Duke dissemination events and partner webinars
Conference submissions and academic manuscripts co-authored by team members and faculty
Foundation for a future external grant proposal on LTC workforce development

Student Opportunities

The team will include 2 graduate students and 8 undergraduate students with interests in global health, sociology, public policy, economics, psychology, aging studies, nursing, data science and communications.

Students will:

Review and analyze LTC policies across several countries
Conduct and analyze surveys, interviews and focus groups
Collaborate with community and international partners in China, the U.S., Singapore, Norway and the U.K.
Create data visualizations, infographics and policy briefs
Prepare academic outputs and present findings at conferences
Participate in DKU-Duke workshops on data visualization, mixed-methods integration and collaborative writing

Students will gain skills in mixed-methods research, data management, comparative policy analysis, ethical fieldwork, cross-cultural communication, dissemination and global teamwork. Graduate students will have opportunities for leadership in project coordination, mentorship, synthesis and manuscript development.

Timing

Summer 2026 – Summer 2027

Summer 2026 (optional):

Onboarding, background review, policy mapping
Establish IRB protocols and partner coordination
Begin data collection and training in AI tools and qualitative methods

Fall 2026:

Continue policy and literature review
Conduct secondary data analysis
Design and pilot survey and interview tools
Begin preliminary data collection

Spring 2027:

Continue and finalize data collection
Analyze survey, interview and secondary data
Integrate cross-country findings
Develop policy briefs, visual materials and dissemination outputs

Summer 2027 (optional):

Finalize cross-site report and digital outputs
Submit student-authored manuscript or conference abstract
Support community dissemination and next-phase proposal development

Crediting

Academic credit available for fall and spring semesters