Research Article| Volume 67, ISSUE 4, P293-301, July 2019

Download started.


Ways of knowing in precision health


      • Including newer data approaches can improve precision health decisions.
      • Omics in research may lead to better assessment and management to improve care.
      • Electronic sensors allow real-time monitoring of behavior and biology in research.
      • Geospatial data provide an important lens to improve precision health approaches.
      • Broader understanding of the complexity of human health and illness will inform health care policy.


      Precision health can provide an avenue to bridge and integrate ways of knowing for research and practice. Nurse scientists have a long-standing interest in using multiple sources of information to address research questions of significance to the profession and discipline of nursing, which can lead to much needed contributions to precision health care. In this paper, nursing scientists discuss emerging research methods including omics, electronic sensors, and geospatial data, and mixed methods that further develop nursing science and contribute to precision health initiatives. The authors provide exemplars of the types of knowledge and ways of knowing that, using these and other advanced data and analytic strategies, may advance precision health within the context of nursing science.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Nursing Outlook
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Abbott S.M.
        • Malkani R.G.
        • Zee P.C.
        Circadian disruption and human health: A bidirectional relationship.
        The European Journal of Neuroscience. 2018;
        • Andrews P.W.
        • Bharwani A.
        • Lee K.R.
        • Fox M.
        • Thomson J.A.
        Is serotonin an upper or a downer? The evolution of the serotonergic system and its role in depression and the antidepressant response.
        Neuroscience and Biobehavioral Reviews. 2015; 51: 164-188
        • Basta L.A.
        • Richmond T.S.
        • Wiebe D.J.
        Neighborhoods, daily activities, and measuring health risks experienced in urban environments.
        Social Science & Medicine. 2010; 71: 1943-1950
        • Bazeley P.
        Integrative analysis strategies for mixed data sources.
        American Behavioral Scientist. 2012; 56: 814-828
        • Bazeley P.
        Integrative analysis in mixed methods research.
        Sage, London2018
        • Bazeley P.
        Mixed methods in my bones”: Transcending the qualitative-quantitative divide.
        International Journal of Multiple Research Approaches. 2018; 10: 334-341
        • Brainard J.
        • Gobel M.
        • Scott B.
        • Koeppen M.
        • Eckle T.
        Health implications of disrupted circadian rhythms and the potential for daylight as therapy.
        Anesthesiology. 2015; 122: 1170-1175
        • Branas C.C.
        • Nance M.L.
        • Elliott M.R.
        • Richmond T.S.
        • Schwab C.W.
        Urban-rural shifts in intentional firearm death: Different causes, same results.
        American Journal of Public Health. 2004; 94: 1750-1755
        • Britt D.W.
        • Evans M.I.
        Sometimes doing the right thing sucks: Frame combinations and multi-fetal pregnancy reduction decision difficulty.
        Social Science & Medicine. 2007; 65: 2342-2356
        • Bryman A.
        Barriers to integrating quantitative and qualitative research.
        Journal of Mixed Methods Research. 2007; 1: 8-22
        • Caiola C.
        • Barroso J.
        • Docherty S.L.
        Capturing the social location of African American mothers living with HIV: An inquiry into how social determinants of health are framed.
        Nursing Research. 2017; 66: 209-221
        • Carper B.A.
        Fundamental patterns of knowing in nursing.
        Advances in Nursing Science. 1978; 1: 13-24
        • Caspi A.
        • Sugden K.
        • Moffitt T.E.
        • Taylor A.
        • Craig I.W.
        • Harrington H.
        • Poulton R.
        Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene.
        Science. 2003; 301: 386-389
        • Chambers D.A.
        • Feero W.G.
        • Khoury M.J.
        Convergence of implementation science, precision medicine, and the learning health care system: A new model for biomedical research.
        Journal of American Medical Association. 2016; 315: 1941-1942
      1. Corwin, E., Dunlop, A. L., Fernandes, J., Li, S., Pearce, B., & Jones, D. P. (2018). Metabolites and metabolic pathways associated with chronic stress exposure in pregnant African American women. Under Review.

        • Corwin E.J.
        • Hogue C.J.
        • Pearce B.
        • Hill C.C.
        • Read T.D.
        • Mulle J.
        • Dunlop A.L.
        BMC Pregnancy Childbirth. 2017; 17: 395
        • Creswell J.W.
        • Plano Clark V.L.
        Designing and conducting mixed methods research.
        Sage Publications, Inc., Thousand Oaks, CA2011
        • DeFranco E.A.
        • Hall E.S.
        • Muglia L.J.
        Racial disparity in previable birth.
        American Journal of Obstetics & Gynecology. 2016; 214 (394.e1–394.e7)
        • Dinan T.G.
        • Cryan J.F.
        The microbiome-gut-brain axis in health and disease.
        Gastroenterology Clinics of North America. 2017; 46: 77-89
        • Docherty S.L.
        • Vorderstrasse A.
        • Brandon D.
        • Johnson C.
        Visualization of multidimensional data in nursing science.
        Western Journal of Nursing Research. 2017; 39: 112-126
        • Dunbar S.
        • Corwin E.
        • Gary R.A.
        • Higgins M.K.
        • Smith A.
        • Butler J.
        Novel correlates of depressive symptoms in family caregivers of heart failure patients.
        Circulation. 2016; 134: A12706
        • Fakhoury M.
        Revisiting the serotonin hypothesis: Implications for major depressive disorders.
        Molecular Neurobiology. 2016; 53: 2778-2786
        • Fetters M.D.
        • Curry L.A.
        • Creswell J.W.
        Achieving integration in mixed methods designs.
        Health Services Research. 2013; 48: 2134-2156
        • Grey M.
        • Rechenberg K.
        Sleep and glycemia in adolescents with type 1 diabetes.
        Diabetes. 2018; 67: A212
        • Jacoby S.F.
        • Tach L.
        • Guerra T.
        • Wiebe D.J.
        • Richmond T.S.
        The health status and well-being of low-resource, housing-unstable, single-parent families living in violent neighbourhoods in Philadelphia.
        Pennsylvania. 2017;
      2. Jeon, S., Conley, S., & Redeker, N. S. (2018). Rest-activity rhythms, sleep disturbance, and functional performance in people with stable heart failure. Under Review.

        • Jeon S.
        • Conley S.
        • Redeker N.S.
        Discrepancy between wrist-actigraph and polysomnographic measures of sleep in patients with stable heart failure and a novel approach to evaluating discrepancy.
        Journal of Sleep Research. 2019; 28: e12717
        • Karg K.
        • Burmeister M.
        • Shedden K.
        • Sen S.
        The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: Evidence of genetic moderation.
        Archives of General Psychiatry. 2011; 68: 444-454
        • Kohane I.S.
        The twin questions of personalized medicine: Who are you and whom do you most resemble?.
        Genome Medicine. 2009; 1: 4
        • Kondo M.C.
        • South E.C.
        • Branas C.C.
        • Richmond T.S.
        • Wiebe D.J.
        The association between urban tree cover and gun assault: A case-control and case-crossover study.
        American Journal of Epidemiology. 2017; 186: 289-296
        • Lutz P.E.
        Multiple serotonergic paths to antidepressant efficacy.
        Journal of Neurophysiology. 2013; 109: 2245-2249
        • Lyles C.R.
        • Lunn M.R.
        • Obedin-Maliver J.
        • Bibbins-Domingo K.
        The new era of precision population health: Insights for the All of Us research program and beyond.
        Journal of Translational Medicine. 2018; 16
        • Martin J.A.
        • Hamilton B.E.
        • Osterman M.J.K.
        • Driscoll A.K.
        • Drake P.
        Births: Final data for 2016.
        National Vital Statistical Report. 2018; 67: 1-55
        • Maxwell J.A.
        The “silo problem” in mixed methods research.
        International Journal of Multiple Research Approaches. 2018; 10: 317-327
        • Mittelstadt B.
        Ethics of the health-related internet of things: A narrative review.
        Ethics and Information Technology. 2017; 19: 157-175
        • National Institute of Nursing Research (U.S.)
        NINR strategic plan.
        National Institute of Nursing Research, Bethesda, MD2016
        • Oberst M.T.
        • Thomas S.E.
        • Gass K.A.
        • Ward S.E.
        Caregiving demands and appraisal of stress among family caregivers.
        Cancer Nursing. 1989; 12: 209-215
        • O'Cathain A.
        • Murphy E.
        • Nicholl J.
        Three techniques for integrating data in mixed methods studies.
        British Medical Journal. 2010; 341: c4587
        • Odgerel Z.
        • Talati A.
        • Hamilton S.P.
        • Levinson D.F.
        • Weissman M.M.
        Genotyping serotonin transporter polymorphisms 5-HTTLPR and rs25531 in European- and African-American subjects from the National Institute of Mental Health's Collaborative Center for Genomic Studies.
        Translational Psychiatry. 2013; 3: e307
        • Onwuegbuzie A.J.
        • Teddlie C.
        A framework for analyzing data in mixed methods research.
        in: Tashakkori A. Teddlie, C C. Handbook of mixed methods in social and behavioral research. Sage, Thousand Oaks, CA2003: 321-350
        • Ordway M.R.
        • Sadler L.S.
        • Canapari C.A.
        • Jeon S.
        • Redeker N.S.
        Sleep, biological stress, and health among toddlers living in socioeconomically disadvantaged homes: A research protocol.
        Research in Nursing & Health. 2017; 40: 489-500
        • Radloff L.S.
        A self-report depression scale for research in the general population.
        Applied Psychological Measurement. 1977; 1: 385-401
        • Risch N.
        • Herrell R.
        • Lehner T.
        • Liang K.Y.
        • Eaves L.
        • Hoh J.
        • Merikangas K.R.
        Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: A meta-analysis.
        Journal of the American Medical Association. 2009; 301: 2462-2471
        • Redeker N.S.
        • Mason D.J.
        • Wykpisz E.
        • Glica B.
        Women's patterns of activity over 6 months after coronary artery bypass surgery.
        Heart & Lung. 1995; 24: 502-511
        • Redeker N.S.
        • Mason D.J.
        • Wykpisz E.
        • Glica B.
        • Miner C.
        First postoperative week activity patterns and recovery in women after coronary artery bypass surgery.
        Nursing Research. 1994; 43: 168-173
        • Redekop W.K.
        • Mladsi D.
        The faces of personalized medicine: A framework for understanding its meaning and scope.
        Value in Health. 2013; 16: S4-S9
        • Rothstein M.A.
        Some lingering concerns about the precision medicine initiative.
        Journal of Law, Medicine & Ethics. 2016; 44: 520-525
        • Salvatore S.
        • Valsiner J.
        Between the general and the unique. Overcoming the nomothetic versus idiographic opposition.
        Theory & Psychology. 2010; 20: 817-833
        • Sandelowski M.
        Unmixing mixed-methods research.
        Research in Nursing and Health. 2014; 37: 3-8
        • Scherman V.
        • Zimmerman L.
        • Smit B.
        Mixed method data analysis: An exploratory approach to strengthening inferences about relationships and affinities.
        International Journal of Multiple Research Approaches. 2018; 10: 57-76
        • Song M.
        • Sandelowski M.
        • Happ M.B.
        Current practices and emerging trends in conducting mixed methods intervention studies in the health sciences.
        in: Tashakkori A. Teddlie C. Sage handbook of mixed methods in social & behavioral research. 2nd ed. Sage, Thousand Oaks, CA2010: 725-747
        • Tach L.
        • Jacoby S.
        • Wiebe D.J.
        • Guerra T.
        • Richmond T.S.
        The effect of microneighborhood conditions on adult educational attainment in a subsidized housing intervention.
        Housing Policy Debate. 2016; 26: 380-397
        • Wiebe D.J.
        • Richmond T.S.
        • Guo W.
        • Allison P.D.
        • Hollander J.E.
        • Nance M.I.
        • Branas C.C.
        Mapping activity patterns to quantify risk of violent assault in urban environments.
        Epidemiology. 2016; 27: 32-41
        • Yang I.
        • Corwin E.J.
        • Brennan P.A.
        • Jordan S.
        • Murphy J.R.
        • Dunlop A.
        The infant microbiome: Implications for infant health and neurocognitive development.
        Nursing Research. 2016; 65: 76-88