Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Sep;62(3):e315-e321.
doi: 10.1016/j.jpainsymman.2021.04.015. Epub 2021 Apr 29.

Objectifying the Subjective: The Use of Heart Rate Variability as a Psychosocial Symptom Biomarker in Hospice and Palliative Care Research

Mallory R Taylor  1 , Samantha R Scott  2 , Angela Steineck  3 , Abby R Rosenberg  3
Affiliations
Review

Objectifying the Subjective: The Use of Heart Rate Variability as a Psychosocial Symptom Biomarker in Hospice and Palliative Care Research

Mallory R Taylor et al. J Pain Symptom Manage. 2021 Sep.

Abstract

Measuring psychosocial symptoms in hospice and palliative care research is critical to understanding the patient and caregiver experience. Subjective patient-reported outcome tools have been the primary method for collecting these data in palliative care, and the growing field of biobehavioral research offers new tools that could deepen our understanding of psychosocial symptomatology. Here we describe one psychosocial biomarker, heart rate variability (HRV), and simple techniques for measurement in an adolescent and young adult cancer population that are applicable to palliative care studies. Complementing self-reported measures with objective biomarkers like HRV could facilitate a more nuanced understanding of physiologic and perceived well-being in patients with serious or life-limiting illness and inform future "precision supportive care" in hospice and palliative medicine.

Keywords: Biomarker; Heart Rate Variability; Palliative Care; Psychosocial.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Extracting R–R intervals from paper ECGs. Paper ECG recordings were scanned to create high-resolution images and uploaded into open-source image processing software (WebPlotDigitizer). R-waves were identified using the software algorithm and manually reviewed for accuracy. R–R intervals were then quantified and used for HRV calculation.
Figure 2.
Figure 2.
Long term (24-hour) HRV recording using the wearable Actiheart device (CamNtech).
See this image and copyright information in PMC

References

    1. Pinquart M and Duberstein PR, Depression and cancer mortality: a meta-analysis. Psychol Med, 2010. 40(11): p. 1797–810. - PMC - PubMed
    1. Felitti VJ, et al. , Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am J Prev Med, 1998. 14(4): p. 245–58. - PubMed
    1. Hawkley LC and Cacioppo JT, Loneliness matters: a theoretical and empirical review of consequences and mechanisms. Ann Behav Med, 2010. 40(2): p. 218–27. - PMC - PubMed
    1. Glaser R and Kiecolt-Glaser JK, Stress-induced immune dysfunction: implications for health. Nat Rev Immunol, 2005. 5(3): p. 243–51. - PubMed
    1. McEwen BS, Stress, adaptation, and disease. Allostasis and allostatic load. Ann N Y Acad Sci, 1998. 840: p. 33–44. - PubMed

Publication types