Health Trajectory Research: A Call to Action for Nursing Science
Henly, Susan J.; Wyman, Jean F.; Gaugler, Joseph E.
Susan J. Henly, PhD, RN, is Professor; Jean F. Wyman, PhD, RN, FAAN, is Professor and Cora Meidl Siehl Endowed Chair in Nursing Research; and Joseph E. Gaugler, PhD, is Associate Professor and McKnight Presidential Fellow, University of Minnesota School of Nursing, Minneapolis.
Accepted for publication March 28, 2011.
Funded in part by the National Institute of Nursing Research (Grant No. P20 NR008992; Center for Health Trajectory Research).
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Nursing Research or the National Institutes of Health.
Corresponding author: Susan J. Henly, PhD, RN, University of Minnesota School of Nursing, 5-140 WDH, 308 Harvard St. SE, Minneapolis, MN 55455 (email@example.com).
The focus of health trajectory research is study of health over time for individual persons, families, or communities. The person-focused, time-based perspective reflects health as it is experienced over the life course and maps directly onto processes of care, contributing to ease in translation of results to practice. The agenda focuses on theoretical and empirical components needed to (a) build health trajectory science; (b) develop the scientific workforce to conduct health trajectory research; (c) integrate health trajectory research with other critical, emerging areas of nursing science (genomics and genetics, informatics, dynamic systems and communication); and (d) apply health trajectory research across the life span and continuum of care. Agenda items point the way toward a reorientation of nursing research that incorporates and emphasizes understanding of individual health trajectories.
Health trajectory research arises from the scholarly discipline of nursing, where the central focus is the study of health. Health trajectory research extends the accepted nursing metaparadigm to incorporate time as a fundamental concept and aligns nursing research models for longitudinal data with methodological standards in related disciplines. The basic approaches illustrated in this supplement refocus nursing science on the person because intraindividual change over time in the personal health experience is the core concern (Henly, 2007). Scientific questions about change in health, the design of time-based health trajectory research projects, and statistical models for health trajectories map onto the processes of professional nursing (from assessment, goal setting, and interventions to outcome evaluation), thus leveraging the potential impact of nursing research findings to improve patient care. The time-based health trajectory perspective informs nursing science across the life-span and across the continuum of care, including health promotion and disease prevention, acute care, and palliative and end-of-life care. In chronic disease, health trajectories provide the groundwork for understanding clinical course and the impact of interventions on disease progression.
The adoption of the health trajectory research perspective will require an increasingly well-prepared scientific workforce in nursing (Henly, 2011). Similar to recent educational changes in biological sciences (National Research Council, 2003), training for a life in nursing science may well need to begin deliberately in the undergraduate years and include mathematics through calculus. Continued discussion of the content of PhD programs in nursing science is required to determine the most efficient ways to develop student knowledge, advance theory (Wohlwill, van Geert, & Mos, 1991; Ram & Gerstorf, 2009) and use the advanced longitudinal approaches needed to capture temporal dynamics in health- and illness-related phenomena. Quantitative course selection and sequencing, integration of the health trajectory content of nursing science with statistical models for longitudinal data, and specialized workshops for developing current nurse scientists' skills may all have their place.
A health trajectory research agenda for person-centered nursing science appears in Table 1. The agenda items identify four areas for action: (a) theoretical and empirical components needed to build health trajectory science, (b) paths to development of the community of scientists in nursing, (c) intersections with innovative and emerging areas of nursing research, and (d) translation of health trajectory findings across the life-span and continuum of care. Action items associated with each area are identified and explained in Table 1.
Conclusion/Call to Action
Health trajectory research is person-centered and reconciles nursing science with the patient-focused perspectives and values in theory and practice. The person-centered health trajectory research agenda paves pathways to this future science. Health trajectory research is an exciting and welcome challenge at the frontiers of nursing science, with promise for improving health across the life-span when findings are translated to practice.
Bakken, S., Stone, P. W., & Larson, E. L. (2008). A nursing informatics research agenda for 2008-18: Contextual influences and key components. Nursing Outlook, 56, 206-215.
Beck, C., McSweeney, J. C., Richards, K. C., Roberson, P. K., Tsai, P.-F., & Souder, E. (2010). Challenges in tailored intervention research. Nursing Outlook, 58, 104-110.
Cairns, R. B., Costello, E. J., & Elder, G. H. Jr. (1996). The making of developmental science. In R. B. Cairns, G. H. Elder, Jr., & E. J. Costello (Eds.), Developmental Science (pp. 223-234). Cambridge, U.K.: Cambridge University Press.
Halfon, N., & Hochstein, M. (2002). Life course health development: An integrated framework for developing health, policy and research. Milbank Quarterly, 80, 447-497.
Henly, S. J. (2007). Lost in time: The person in nursing research [Editorial]. Nursing Research
Henly, S. J. (2011). The future history of nursing science: 2026. [Editorial]. Nursing Research
Jenkins, J., Grady, P. A., & Collins, F. S. (2005). Nurses and the genomic revolution. Journal of Nursing Scholarship
Lea, D. H., Skirton, H., Read, C. Y., & Williams, J. K. (2011). Implications for educating the next generation of nurses on genetics and genomics in the 21st century. Journal of Nursing Scholarship
Little, T. D., Bovaird, J. A., & Card, N. A. (2007). Modeling contextual effects in longitudinal studies. Mahwah, NJ: Erlbaum.
McLeod, J. D., & Shanahan, M. J. (1996). Trajectories of poverty and children's mental health. Journal of Health and Social Behavior
Meleis, A. I., Sawyer, L. M., Im, E.-O., Hilfinger Messias, D. K., & Schumacher, K. (2000). Experiencing transition: An emerging middle-range theory. Advances in Nursing Science
National Research Council, Committee on Undergraduate Biology Education to Prepare Research Scientists for the 21st Century. (2003). BIO2010: Transforming undergraduate education for future research biologists
. Washington, DC: National Academies Press.
Naylor, M. D., Kutzman, E. T., & Pauly, M. V. (2009). Transitions of elders between long-term care and hospitals. Policy, Politics, & Nursing Practice, 10, 187-194.
Patient Protection and Affordable Care Act of 2010, Pub. L. No. 111-148, Part III Staff Training, Subtitle D Patient-Centred Outcomes Research (2011).
Patient Reported Outcome Measurement Information System. (n.d.). Validity studies (previously Wave II) Testing. Retrieved March 13, 2011, from http://www.nihpromis.org/Web
Ram, N., & Gerstorf, D. (2009). Methods for the study of development-Developing methods. Research in Human Development
Shortreed, S. M., Laber, E., Lizotte, D. J., Strioup, T. S., Pineau, J., & Murphy, S. A. (2010). Informing sequential clinical decision-making through reinforcement learning: An empirical study. Machine Learning
. doi: 10.1007/s10994-010-5229-0. Retrieved from http://www.springerlink.com/content/61364524708h76g7/
Steen, L. (2004). Achieving quantitative literacy. An urgent challenge for higher education. Washington, DC: The Mathematical Association of America.
Stewart, B. J., & Archbold, P. G. (1992). Nursing intervention studies require outcome measures that are sensitive to change: Part one. Research in Nursing and Health
Stewart, B. J., & Archbold, P. G. (1993). Nursing intervention studies require outcome measures that are sensitive to change: Part two. Research in Nursing and Health
Tsiatis, A. A., & Davidian, M. (2004). Joint modeling of longitudinal and time-to-event data: An overview. Statistica Sinica
Walls, T. A., & Schafer, J. L. (Eds.) (2006). Models for intensive longitudinal data. Oxford, U.K.: Oxford University Press.
Wohlwill, J. F., van Geert, P., & Mos, L. P. (1991). Relations between method and theory in developmental research: A partial-isomorphism view. Annals of Theoretical Psychology
applied longitudinal data analysis; health trajectory; nursing research agenda
© 2011 Lippincott Williams & Wilkins, Inc.
Highlight selected keywords in the article text.