{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T00:54:03Z","timestamp":1755219243430,"version":"3.43.0"},"reference-count":20,"publisher":"Georg Thieme Verlag KG","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Patient mobility during hospitalization is essential for high-quality healthcare as mobility is linked to physical function and quality of life. The Johns Hopkins Highest Level of Mobility (JH-HLM) scale is a validated method to assess mobility in hospitalized patients. Although the JH-HLM is widely utilized, it has limitations including ceiling effects, unobserved mobility events going unrecorded, and the staff time needed to observe and document.<\/jats:p><jats:p>We explored the feasibility of using a consumer-grade activity monitor (Fitbit) to predict JH-HLM scores and address these limitations.<\/jats:p><jats:p>JH-HLM scores and step counts were recorded simultaneously using behavioral mapping and analyzed over 1-hour periods among inpatients. We predicted JH-HLM scores based on step counts by fitting ordinal logistic regressions, according to three categorizations of JH-HLM scores reflecting increasing mobility-granularity.<\/jats:p><jats:p>We collected data for 189 patient-hours in a cohort of 20 participants. Step counts increased with higher JH-HLM mobility scores. When predicting JH-HLM scores from step counts, there was a trade-off between accuracy and mobility granularity: overall accuracy was 75% when categorizing patient-hours as immobility (JH-HLM of 1 to 5) or mobility (JH-HLM of 6 to 8); accuracy was 68% when categorizing immobility, shorter walking behavior (JH-HLM of 6 to 7), and longer walking behavior (JH-HLM of 8); accuracy was 61% when categorizing immobility and three progressively higher volumes of walking (JH-HLM of 6, 7 and 8).<\/jats:p><jats:p>Step counts from the activity monitor could be used to predict whether a patient was immobile or mobile but may lack the sensitivity to accurately predict specific mobility levels.<\/jats:p>","DOI":"10.1055\/a-2576-1505","type":"journal-article","created":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T22:59:07Z","timestamp":1754521147000},"page":"753-759","source":"Crossref","is-referenced-by-count":0,"title":["From Steps to Mobility Levels: Validating a Consumer-Grade Activity Monitor for Automated Recording of Patient Mobility in Hospitals"],"prefix":"10.1055","volume":"16","author":[{"given":"Jan","family":"Stenum","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Stewart","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel L.","family":"Young","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States"},{"name":"Department of Physical Therapy, University of Nevada Las Vegas, Las Vegas, Nevada, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Collector","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karli","family":"Funk","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins Hospital, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lydia","family":"Vincent","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins Hospital, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth","family":"Colantuoni","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik H.","family":"Hoyer","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"194","published-online":{"date-parts":[[2025,8,6]]},"reference":[{"issue":"01","key":"ref1","first-page":"7840743","article-title":"Effectiveness, safety, and barriers to early mobilization in the intensive care unit","volume":"2020","author":"G K Alaparthi","year":"2020","journal-title":"Crit Care Res Pract"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"151655","DOI":"10.1016\/j.apnr.2022.151655","article-title":"A unit-based, multi-center evaluation of adopting mobility measures and daily mobility goals in the hospital setting","volume":"70","author":"E H 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