Advancing Nursing Science Through Health Trajectory Research: An Introduction
Wyman, Jean F.; Henly, Susan J.
Jean F. Wyman, PhD, RN, FAAN, is Professor and Cora Meidl Siehl Endowed Chair in Nursing Research; and Susan J. Henly, PhD, RN, is Professor, University of Minnesota School of Nursing, Twin Cities.
Accepted for publication March 4, 2011.
This study was funded in part by the National Institute of Nursing Research (Grant No. P20 NR008992; Center for Health Trajectory Research) and the Office of the Senior Vice President, Academic Health Center, University of Minnesota, Minneapolis.
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: Jean F. Wyman, PhD, RN, FAAN, University of Minnesota School of Nursing, Minneapolis, MN 55455 (e-mail: firstname.lastname@example.org).
Abstract: The Minnesota Center for Health Trajectory Research has focused on developing ways to better understand how interventions influence health trajectories during transitional, acute, or chronic health challenges across the life span. The health trajectory perspective advances nursing science by providing a person-centered point of view that emphasizes change in health over time within individuals, families, groups, or communities. Theoretical considerations and statistical modeling approaches used in studying health trajectories, along with exemplars from nursing research studies from this special issue of Nursing Research, are highlighted.
The science of preventive and therapeutic interventions has advanced rapidly over the past several decades. However, gaps in knowledge remain related to the promotion and restoration of optimal health and quality of life of individuals and families across the life span. Explicating the impact of preventive and therapeutic interventions on health in individuals over time is a significant focus needed for gaining a more complete understanding of experienced health and how to influence health outcomes. The pattern of health over time is called a health trajectory.
This Nursing Research supplement is a compendium of commentary and primary reports assembled to provide a cohesive introduction to health trajectory research. The collection of articles provides novel perspectives on the dynamic course of health. The articles illustrate how the health trajectory perspective can be used to extend existing programs of nursing research and develop new areas of investigation for nursing science. Using the health trajectory perspective, new intervention strategies aimed at influencing health over time, rather than at a single point in time, can be developed for clinical practice.
Minnesota Center for Health Trajectory Research
Articles in this supplement reflect the efforts of the Minnesota Center for Health Trajectory Research (MCHTR), an exploratory research center funded by the National Institute of Nursing Research (P20 NR008992; 2005-2011). The MCHTR supported the development of nursing intervention science focused on the promotion, maintenance, and restoration of health over time. The goal was to develop ways to better understand how interventions influence health trajectories experienced by individuals, families, groups, or communities with transitional, acute, or chronic health challenges across the life span (National Institute of Mental Health, 2010; National Institute of Nursing Research, 2006, 2011). The notion of the health trajectory (course of health over time) links the research of MCHTR investigators working to advance nursing science using the person-centered point of view (Henly, 2007; Kent & Hayward, 2007) needed for the application of findings from intervention research into health services.
The MCHTR conceptual framework (Figure 1) is an adaptation of the determinants of health model that was used as the foundation for identifying Healthy People 2010 (U.S. Department of Health and Human Services, 2000) needs and goals. The framework shows that health outcomes for individuals and families are influenced by biological or genetic factors and behavior nested within physical and social environments, including health services. The addition of a time line emphasizes the critical temporal perspective of the work of MCHTR. Deliberate addition of the temporal dimension to the determinants of health model set the stage for health trajectory research needed to undergird the current Healthy People 2020 initiatives because healthy development and health behaviors across the life span and within life stages, especially adolescence, early and middle childhood, and older adulthood, are emphasized (Guyton-Krishnan, 2010). The temporally focused determinants of health framework was used to inform MCHTR investigations of health over time.
Health Over Time
Many health phenomena are dynamic (i.e., they change over time). These health trajectories may be amenable to nursing intervention. Developmental trajectories (including life transitions) include normal physiological changes such as puberty, menopause, and aging (Clipp, 2006) and their associated psychological responses (Schumacher, Jones, & Meleis, 1999; Woods, Mariella, & Mitchell, 2002); reproductive events, such as pregnancy and childbirth along with acquisition of parenting skills (Chang & Fine, 2007; Skipstein, Janson, Stoolmiller, & Mathiesen, 2010); marital quality and events (Anderson, Van Ryzin, & Dougherty, 2010); and life transitions such as adolescence (Lynne-Landsman, Bradshaw, & Ialongo, 2010), retirement (Minkler, 1981), and death of a family member (Bonanno, Wortman, & Nesse, 2004). Caregiving experiences, such as parenting a child with chronic or special healthcare needs (Swallow & Jacoby, 2001) and providing care for an aging spouse or parent with disability or illness, are also considered developmental trajectories (Burton, Zdaniuk, Schultz, Jackson, & Hirsch, 2003). Acute illness trajectories are associated with abrupt onset of illness with short courses, emergency events such as trauma and other life-threatening conditions (e.g., myocardial infarction), surgical interventions, and specific treatments that cause time-delimited effects (e.g., chemotherapy, radiation therapy, or bone marrow transplants) as well as exacerbation of chronic diseases such as an acute flare-up of multiple sclerosis or delirium superimposed on dementia (Forsyth, Salorio, & Christensen, 2010; Kim, Barsevick, & Tulman, 2009). The course of acute illnesses sometimes follows predictable patterns of symptom or symptom cluster occurrence such that the treatment of underlying pathophysiology tends to resolve or mitigate symptoms.
Chronic illness trajectories are those associated with an acute event that results in irreversible damage, such as a stroke or spinal cord injury, or a long-standing progressive disease, such as diabetes mellitus, schizophrenia, or Parkinson's disease, with or without functional disabilities that tend to worsen over time (Cullen et al., 2011; Dibble et al., 2010; Kirkevold, 2002). Although treatment may help slow the progression of a specific chronic disease, manage its associated symptoms, and prevent exacerbations and complications, it will not cure the disease or eradicate the underlying pathophysiology. These trajectories tend to be more variable from person to person. However, an individual with chronic illness can achieve positive health outcomes with appropriate management (Hymovich & Hagopian, 1991; Strauss et al., 1984; Woog, 1992). Disability trajectories describe pathways to disablement (Pope & Tarlov, 1991; Verbrugge & Jette, 1994; World Health Organization, 2001) that have the potential for being arrested or reversed through rehabilitation and other forms of intervention (West, Hill, Hewlson, Knapp, & House, 2010). End-of-life or dying trajectories can occur across the life span and result from acute and traumatic illness, chronic disease, and normal aging changes in combination with comorbidity (Covinsky, Eng, Lui, Sands, & Yaffe, 2003; Steele, 2000). Having a better understanding of these various health trajectories and how they can be shaped through interventions will help clinicians provide better care for individuals and families at all stages of their lives.
Articles in This Supplement
Most of the articles in this supplement were presented at either MCHTR-sponsored symposia at the 2008 Council for the Advancement of Nursing Science's State of Science Congress ("Modeling Health Trajectories: Launching Person-Centered Research for Nursing Science") or at the 2009 Midwest Nursing Research Society's Annual Conference ("Symptom Interventions: Studying Impact Over Time"). Each article proposal was initially reviewed conceptually by the editors. Submitted articles then underwent rigorous peer review. Each article had a minimum of three reviewers, with at least one reviewer having statistical expertise in the longitudinal methods in the article. In preparation of their articles or critiques, authors, editors, and reviewers followed guidelines that had been prepared for this supplement to help ensure that analytical methods and presentation of results clearly reflected health trajectory research methodology. We are grateful for the scientific expertise of the 21 reviewers from 20 institutions in three countries who participated in the peer review process. Their insightful critiques, comments, and suggestions were invaluable in creating this supplement.
The content begins with an exposition of the health trajectory perspective in nursing science. Theoretical considerations in studying health and illness over time are outlined, and advances in statistical modeling that support the development of this line of inquiry are introduced (Henly, Wyman, & Findorff, this issue).
The primary reports show an application of the trajectory perspective across a wide range of observational and experimental nursing research studies in populations across the life span; in health and illness; studied in community, hospital, and laboratory settings; and across time scales from seconds to years. Whether describing the natural history of some health experience or assessing the impact of an intervention on health over time, theory about change, temporal design of the study, and the statistical model describing the impact of time on health are linked to emphasize the individual health-illness experience. Parasympathetic nervous system functioning in infants after surgical repair of congenital heart defects was described by monitoring heart rate variability continuously during feeding (Harrison, this issue). Condom use consistency during adolescence was studied as part of a clinic-based intervention designed to prevent early pregnancy among sexually active girls (Bearinger Sieving, Duke, McMorris, Stoddard, & Pettingell, this issue). Anxiety was measured daily after intubation during adult intensive care and modeled to better understand course over time as a foundation for determining optimal management approaches using nonpharmacological (e.g., music) and anxiolytic (e.g., sedation) therapies (Chlan & Savik, this issue). Self-reported gastrointestinal symptoms associated with fiber supplementation interventions for community-dwelling adults with fecal incontinence were studied daily throughout the phases of a clinical trial to better understand the ongoing experiences of participants and the link with study attrition (Bliss, Savik, Jung, Whitebird, & Lowry, this issue). Among people with peripheral arterial disease, pain reported on an ordinal scale every 30 seconds during treadmill testing before and after 12-week exercise interventions in a clinical trial revealed differences in personal trajectories of claudication at baseline that influenced the impact of the experimental effects observed at posttest (Treat-Jacobsen, Henly, Bronas, Leon, & Henly, this issue). Caregiving burden and depression measured annually for over 9 years were used to characterize the effect of transition to nursing home care of spouses with dementia (Gaugler, Roth, Haley, & Mittleman, this issue). The nature of change (the trajectories) varied widely across the studies, but the expectation was that interindividual differences in intraindividual change would emerge.
This supplement concludes with our vision for future health trajectory research (Henly, Wyman, & Gaugler, this issue). Priority areas of application are identified in light of current nursing knowledge and the developing strategic plan for the National Institute of Nursing Research. The agenda includes recommendations for strengthening methodological training in PhD programs in nursing to ensure that future nurse scientists will be well prepared to use these methods.
We believe that these articles will provide ideas for nurse researchers on how to incorporate a health trajectory perspective into the design and analysis of future intervention studies, especially to better understand how protocols are influencing individual course. Health trajectory science provides the knowledge needed to personalize care in practice, from the design of clinical assessment protocols to the creation and evaluation of interventions tailored for individuals and adapted in real time at points of care to optimize outcomes. As illustrated in this supplement, the health trajectory perspective opens new horizons for the creation of a person-centered nursing science by deliberately and thoughtfully incorporating time into observation protocols and experiments in nursing research.
Anderson, J. R., Van Ryzin, M. J., & Dougherty, W. J. (2010). Developmental trajectories of marital happiness in continuously married individuals: A group-based modeling approach. Journal of Family Psychology
Bonanno, G. A., Wortman, C. B., & Nesse, R. M. (2004). Prospective patterns of resilience and maladjustment during widowhood. Psychology and Aging
Burton, L. C., Zdaniuk, B., Schultz, R., Jackson, S., & Hirsch, C. (2003). Transitions in spousal caregiving. Gerontologist
Chang, Y., & Fine, M. A. (2007). Modeling parenting stress trajectories among low-income young mothers across the child's second and third years: Factors accounting for stability and change. Journal of Family Psychology
Clipp, E. C. (2006, October). Frontiers in aging research
. Paper presented at the National Congress on the State of the Science Nursing Research Conference, Washington, DC.
Covinsky, K. E., Eng, C., Lui, L. Y., Sands, L. P., & Yaffe, K. (2003). The last 2 years of life: Functional trajectories of frail older people. Journal of the American Geriatrics Society
Cullen, K., Guimaraes, A., Wozniak, J., Anjum, A., Schulz, S. C., & White, T. (2011). Trajectories of social withdrawal and cognitive decline in the schizophrenia prodrome. Clinical Schizophrenia & Related Psychoses
Dibble, L. E., Cavanaugh, J. T., Earhart, G. M., Ellis, T. D., Ford, M. P., & Foreman, K. B. (2010). Charting the progression of disability in Parkinson disease: Study protocol for a prospective longitudinal cohort study. BMC Neurology
Forsyth, R. J., Salorio, C. F., & Christensen, J. R. (2010). Modelling early recovery patterns after paediatric traumatic brain injury. Archives of Disease in Childhood
Henly, S. J. (2007). Lost in time. The person in nursing research [Editorial]. Nursing Research
Hymovich, D. P., & Hagopian, G. A. (1991). Chronic illness in children and adults. A psychosocial approach.
Kent, D., & Hayward, R. (2007). When averages hide individual differences in clinical trials. American Scientist
Kim, H. J., Barsevick, A. M., & Tulman, L. (2009). Predictors of the intensity of symptoms in a cluster in patients with breast cancer. Journal of Nursing Scholarship
Kirkevold, M. (2002). The unfolding illness trajectory of stroke. Disability and Rehabilitation
Lynne-Landsman, S. D., Bradshaw, C. P., & Ialongo, N. S. (2010). Testing a developmental model of adolescent substance use trajectories and young adult adjustment. Development and Psychopathology
Minkler, M. (1981). Research on the health effects of retirement: An uncertain legacy. Journal of Health and Social Behavior
Pope, A. M., & Tarlov, A. R. (Eds.). (1991). Disability in America. Toward a national agenda for prevention
. Washington, DC: National Academy Press.
Schumacher, K. L., Jones, P. S., & Meleis, A. I. (1999). Helping elderly persons in transition: A framework for research and practice. In E. Swanson, & T. Tripp-Reimer, (Eds). Life transition in the older adult: Issues for nurses and other health professionals
(pp. 1-26). New York: Springer.
Skipstein, A., Janson, H., Stoolmiller, M., & Mathiesen, K. S. (2010). Trajectories of maternal symptoms of anxiety and depression. A 13-year longitudinal study of a population-based sample. BMC Public Health
Steele, R. G. (2000). Trajectory of certain death at an unknown time: Children with neurodegenerative life-threatening illnesses. Canadian Journal of Nursing Research
Strauss, A. L., Corbin, J., Fagerhaug, S., Glaser, B. G., Maines, D., Suczek, B., et al. (1984). Chronic illness and the quality of life
(2nd ed.). St. Louis, MO: Mosby.
Swallow, V. M., & Jacoby, A. (2001). Mothers' evolving relationships with doctors and nurses during the chronic childhood illness trajectory. Journal of Advanced Nursing
U.S. Department of Health and Human Services. (2000). Healthy People 2010: Understanding and improving health
(2nd ed.). Washington, DC: U.S. Government Printing Office.
Verbrugge, L. M., & Jette, A. M. (1994). The disablement process. Social Science & Medicine
West, R., Hill, K., Hewlson, J., Knapp, P., & House, A. (2010). Psychological disorders after stroke are an important influence on functional outcomes: A prospective cohort study. Stroke
Woods, N. F., Mariella, A., & Mitchell, E. S. (2002). Patterns of depressed mood across the menopausal transition: Approaches to studying patterns in longitudinal data. Acta Obstetricia et Gynecologica Scandinavica
Woog, P. (Ed.). (1992). The chronic illness trajectory framework: The Corbin and Strauss Nursing Model
. New York: Springer.
World Health Organization. (2001). International classification of functioning, disability and health: ICF.
Geneva, Switzerland: Author.
developmental research centers; health trajectory
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