Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study
BackgroundDescribing changes in health and behavior that precede and follow a sentinel health event, such as a cancer diagnosis, is challenging because of the lack of longitudinal, objective measurements that are collected frequently enough to capture varying trajectories of...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2023-08-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2023/1/e45693 |
| _version_ | 1797745685319122944 |
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| author | Chao-Yi Wu Deanne Tibbitts Zachary Beattie Hiroko Dodge Jackilen Shannon Jeffrey Kaye Kerri Winters-Stone |
| author_facet | Chao-Yi Wu Deanne Tibbitts Zachary Beattie Hiroko Dodge Jackilen Shannon Jeffrey Kaye Kerri Winters-Stone |
| author_sort | Chao-Yi Wu |
| collection | DOAJ |
| description |
BackgroundDescribing changes in health and behavior that precede and follow a sentinel health event, such as a cancer diagnosis, is challenging because of the lack of longitudinal, objective measurements that are collected frequently enough to capture varying trajectories of change leading up to and following the event. A continuous passive assessment system that continuously monitors older adults’ physical activity, weight, medication-taking behavior, pain, health events, and mood could enable the identification of more specific health and behavior patterns leading up to a cancer diagnosis and whether and how patterns change thereafter.
ObjectiveIn this study, we conducted a proof-of-concept retrospective analysis, in which we identified new cancer diagnoses in older adults and compared trajectories of change in health and behaviors before and after cancer diagnosis.
MethodsParticipants were 10 older adults (mean age 71.8, SD 4.9 years; 3/10, 30% female) with various self-reported cancer types from a larger prospective cohort study of older adults. A technology-agnostic assessment platform using multiple devices provided continuous data on daily physical activity via wearable sensors (actigraphy); weight via a Wi-Fi–enabled digital scale; daily medication-taking behavior using electronic Bluetooth-enabled pillboxes; and weekly pain, health events, and mood with online, self-report surveys.
ResultsLongitudinal linear mixed-effects models revealed significant differences in the pre- and postcancer trajectories of step counts (P<.001), step count variability (P=.004), weight (P<.001), pain severity (P<.001), hospitalization or emergency room visits (P=.03), days away from home overnight (P=.01), and the number of pillbox door openings (P<.001). Over the year preceding a cancer diagnosis, there were gradual reductions in step counts and weight and gradual increases in pain severity, step count variability, hospitalization or emergency room visits, and days away from home overnight compared with 1 year after the cancer diagnosis. Across the year after the cancer diagnosis, there was a gradual increase in the number of pillbox door openings compared with 1 year before the cancer diagnosis. There was no significant trajectory change from the pre– to post–cancer diagnosis period in terms of low mood (P=.60) and loneliness (P=.22).
ConclusionsA home-based, technology-agnostic, and multidomain assessment platform could provide a unique approach to monitoring different types of behavior and health markers in parallel before and after a life-changing health event. Continuous passive monitoring that is ecologically valid, less prone to bias, and limits participant burden could greatly enhance research that aims to improve early detection efforts, clinical care, and outcomes for people with cancer. |
| first_indexed | 2024-03-12T15:27:40Z |
| format | Article |
| id | doaj.art-8452448f912b4afc96918276d8e6f9ab |
| institution | Directory Open Access Journal |
| issn | 2561-326X |
| language | English |
| last_indexed | 2024-03-12T15:27:40Z |
| publishDate | 2023-08-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj.art-8452448f912b4afc96918276d8e6f9ab2023-08-10T12:46:13ZengJMIR PublicationsJMIR Formative Research2561-326X2023-08-017e4569310.2196/45693Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series StudyChao-Yi Wuhttps://orcid.org/0000-0002-2187-6509Deanne Tibbittshttps://orcid.org/0000-0001-6186-8338Zachary Beattiehttps://orcid.org/0000-0002-4844-7122Hiroko Dodgehttps://orcid.org/0000-0001-7290-8307Jackilen Shannonhttps://orcid.org/0000-0001-5377-9511Jeffrey Kayehttps://orcid.org/0000-0002-9971-3478Kerri Winters-Stonehttps://orcid.org/0000-0003-1706-8020 BackgroundDescribing changes in health and behavior that precede and follow a sentinel health event, such as a cancer diagnosis, is challenging because of the lack of longitudinal, objective measurements that are collected frequently enough to capture varying trajectories of change leading up to and following the event. A continuous passive assessment system that continuously monitors older adults’ physical activity, weight, medication-taking behavior, pain, health events, and mood could enable the identification of more specific health and behavior patterns leading up to a cancer diagnosis and whether and how patterns change thereafter. ObjectiveIn this study, we conducted a proof-of-concept retrospective analysis, in which we identified new cancer diagnoses in older adults and compared trajectories of change in health and behaviors before and after cancer diagnosis. MethodsParticipants were 10 older adults (mean age 71.8, SD 4.9 years; 3/10, 30% female) with various self-reported cancer types from a larger prospective cohort study of older adults. A technology-agnostic assessment platform using multiple devices provided continuous data on daily physical activity via wearable sensors (actigraphy); weight via a Wi-Fi–enabled digital scale; daily medication-taking behavior using electronic Bluetooth-enabled pillboxes; and weekly pain, health events, and mood with online, self-report surveys. ResultsLongitudinal linear mixed-effects models revealed significant differences in the pre- and postcancer trajectories of step counts (P<.001), step count variability (P=.004), weight (P<.001), pain severity (P<.001), hospitalization or emergency room visits (P=.03), days away from home overnight (P=.01), and the number of pillbox door openings (P<.001). Over the year preceding a cancer diagnosis, there were gradual reductions in step counts and weight and gradual increases in pain severity, step count variability, hospitalization or emergency room visits, and days away from home overnight compared with 1 year after the cancer diagnosis. Across the year after the cancer diagnosis, there was a gradual increase in the number of pillbox door openings compared with 1 year before the cancer diagnosis. There was no significant trajectory change from the pre– to post–cancer diagnosis period in terms of low mood (P=.60) and loneliness (P=.22). ConclusionsA home-based, technology-agnostic, and multidomain assessment platform could provide a unique approach to monitoring different types of behavior and health markers in parallel before and after a life-changing health event. Continuous passive monitoring that is ecologically valid, less prone to bias, and limits participant burden could greatly enhance research that aims to improve early detection efforts, clinical care, and outcomes for people with cancer.https://formative.jmir.org/2023/1/e45693 |
| spellingShingle | Chao-Yi Wu Deanne Tibbitts Zachary Beattie Hiroko Dodge Jackilen Shannon Jeffrey Kaye Kerri Winters-Stone Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study JMIR Formative Research |
| title | Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study |
| title_full | Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study |
| title_fullStr | Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study |
| title_full_unstemmed | Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study |
| title_short | Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study |
| title_sort | using continuous passive assessment technology to describe health and behavior patterns preceding and following a cancer diagnosis in older adults proof of concept case series study |
| url | https://formative.jmir.org/2023/1/e45693 |
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