Arizona Nurse - April 2021
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<strong>April</strong>, May, June <strong>2021</strong> <strong>Arizona</strong> <strong>Nurse</strong> • Page 9<br />
Family Caregiving Context: A Pilot Study<br />
Rachel L. Peterson, PhD, MPH, MA<br />
Division of Epidemiology, Public Health Sciences<br />
University of California, Davis<br />
Kim D. Shea, PhD, RN, CHPN, College of Nursing<br />
Jian Liu, PhD, Department of Systems and Industrial Engineering<br />
Kayla Luque, BSN Student, College of Nursing<br />
Jessica Powell, BSN Student, College of Nursing<br />
Yinwei Zhang, PhD Student, Department of Systems and Industrial Engineering<br />
Deborah K. Williams, PhD, MPH, RN, College of Nursing<br />
Lori Martin-Plank, PhD, FNP-BC, NP-C, GNP-BC, FAANP, FNAP, College of Nursing<br />
Beverly J. Heasley, MBA, RN, FNGNA, College of Nursing<br />
Linda R. Phillips, PhD, RN, FGSA, Center on Aging<br />
Janice D. Crist, PhD, RN, FWAN, FAAN, College of Nursing<br />
The University of <strong>Arizona</strong><br />
Small changes in older adults’ lives can lead to “tipping points,”<br />
permanently altering health and wellbeing. A “caregiving tipping<br />
point” is a catastrophic event, e.g., a fall with a fracture. Such events<br />
can change older adults’ self-care ability, increase family burden, and<br />
lead to breakdowns of caregiving systems and living arrangements.<br />
Although tipping points appear to be sudden, they are often preceded<br />
by small changes that could have been identified (Crist, Liu et al., 2019).<br />
We seek to predict tipping points with data collected by an affordable<br />
fitness watch, questionnaires, and in-person interviews. In this pilot<br />
study, we investigated if this approach was sufficient to develop tipping<br />
point algorithms and if Mexican American (MA) caregiving families<br />
(older adults and family caregivers) found these activities acceptable.<br />
We focused on MA families because they are less likely than non-Latino<br />
white families to access and utilize long-term support services for many<br />
reasons, including familismo, i.e., “We take care of our own,” and a lack<br />
of trust or culturally tailored information about services (Crist, Ortiz-<br />
Dowling et al., 2019). Also, MA individuals experience more disability at<br />
earlier ages than others (Tarraf et al., 2020).<br />
We recruited MA older adults from local congregate meal sites. We<br />
visited participants in their homes at the beginning and end of one<br />
week. Participants provided demographics and completed a modified<br />
Life Space Questionnaire (LSQ), mapping their regular steps in the home<br />
and the community. Throughout the week, participants completed a<br />
daily diary to record their activities at specific times throughout the day,<br />
noting abnormalities in how they felt, e.g., dizziness, pain. Participants<br />
wore the watch continuously for seven days. Then researchers visited<br />
to download watch and LSQ data, collect diaries, and interview the<br />
older adult. Participants received $30 and kept the watch. The research<br />
was approved by the University of <strong>Arizona</strong> Institutional Review Board.<br />
Engineers analyzed watch data to detect how much variation<br />
occurred during the week, comparing these findings with participants’<br />
self-reported activities. Engineers used “continuous wavelet transform<br />
analysis” (Nason, 2008) to identify daily step counts, continuous heart<br />
rate, and patterns. The daily dairies aided the interpretation of the watch<br />
data. We used content analysis (Neuendorf, 2002) to identify themes<br />
from the interviews about experiences wearing the watch.<br />
Results from this pilot study of seven MA women ages 58-84 suggest<br />
this method is appropriate for detection of changes in heart rate data<br />
among older adults. However, variations in pedometer data were too<br />
limited to explain the observed variations in participants’ heart rates,<br />
e.g., abrupt changes in heart rate and their extent. The daily diary<br />
information varied widely, limiting the diaries’ usefulness.<br />
Wearing the watch 24 hours/day was acceptable, simple, comfortable,<br />
and familiar. It motivated the women to engage in more physical<br />
activity. Several used the watch to monitor their daily step count to<br />
reach movement goals. Participants noted social benefits and barriers.<br />
One felt “special” by participating in the study and receiving the watch.<br />
Another feared she might become alienated from friends not wearing a<br />
watch. Most participants indicated they relied on younger relatives to<br />
help with technology, although some were interested in learning to use<br />
the technology more effectively.<br />
Findings are a critical step towards predicting tipping points. When<br />
the predictive ability of continuous data becomes more useable,<br />
nurses can better assist community-dwelling older adults to “age in<br />
place.” More sophisticated, but less affordable, watches that collect<br />
additional biometric data may be necessary to develop sensitive and<br />
reliable tipping point algorithms. Early identification of tipping points,<br />
e.g., an older adults’ decreasing mobility, and becoming vulnerable to<br />
falls, could alert nurses and families that it’s time to access services<br />
to prevent catastrophes. This study with MA older adults provides a<br />
template for future research. Contrary to popular assumptions, the<br />
majority of Latino individuals access the Internet through mobile phones<br />
and Latino caregivers access the Internet daily to communicate and find<br />
information (Iribarren et al., 2019). However, the cost of technology will<br />
need to be balanced with its capacity to ensure use while providing<br />
sufficient data to predict tipping points. New findings may guide nurses,<br />
researchers, and policymakers to offer culturally tailored interventions<br />
for supporting older adults’ aging in place.<br />
References<br />
Crist, J. D., Liu, J., Shea, K. D., Peterson, R. L., Martin-Plank, L., Lacasse, C. L.,<br />
. . . Phillips, L. R. (2019). “Tipping point” concept analysis in the family<br />
caregiving context. Nursing Forum, 54(4), 582-592.<br />
Crist, J. D., Ortiz-Dowling, E. M., Shea, K. D., & Phillips, L. R. (2019).<br />
Knowledge Gaps About End-of-Life Decision Making Among Mexican<br />
American Older Adults and Their Family Caregivers: An Integrative<br />
Review. In Journal of Transcultural Nursing (Vol. 30, Issue 4, pp. 380-393).<br />
SAGE Publications Inc. https://doi.org/10.1177/1043659618812949<br />
Iribarren, S., Stonbraker, S., Suero-Tejeda, N., Granja, M., Luchsinger,<br />
J. A., Mittelman, M., Bakken, S., & Lucero, R. (2019). Information,<br />
communication, and online tool needs of Hispanic family caregivers of<br />
individuals with Alzheimer’s disease and related dementias. Informatics<br />
for Health and Social Care, 44(2), 115–134. https://doi.org/10.1080/175381<br />
57.2018.1433674<br />
Nason, G. (2008). Wavelet methods in statistics with R. Springer.<br />
Neuendorf, K. A. (2002). Defining Content Analysis. In The Content Analysis<br />
Guidebook (pp. 1–35). https://doi.org/10.4135/9781071802878.n1<br />
Tarraf, W., Jensen, G. A., Dillaway, H. E., Vásquez, P. M., & González, H. M.<br />
(2020). Trajectories of Aging among U.S. Older Adults: Mixed Evidence<br />
for a Hispanic Paradox. Journals of Gerontology - Series B Psychological<br />
Sciences and Social Sciences, 75(3), 601–612. https://doi.org/10.1093/<br />
geronb/gby057<br />
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