Patient-Reported Mobility: A Systematic Review

Pinto‐Carral, Arrate; Fernández‐Villa, Tania; Torre, Antonio José Molina de la

doi:10.1016/j.apmr.2016.01.025

Cited by 19 publications

(12 citation statements)

References 63 publications

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“…Mobility at large has traditionally been studied using self-report questionnaires on the perceived ability and capacity of individuals (i.e., what an individual could do or has done) or through performance-based tests in clinical settings ( 9 ). While some of these instruments provide an acceptable illustration of the relationship between perceived ability, capacity, and performance measures of function ( 10 ), these measures do not necessarily translate into actual real-life performance ( 11 ). Several studies have shown that they in fact remain a poor proxy of real life mobility of an individual, as they fail to capture the dynamics between the environment, the intrapersonal factors of mobility restriction and the real life expression of this mobility ( 12 ).…”

Section: Introductionmentioning

confidence: 99%

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors

Boissy

Blamoutier

Brière

et al. 2018

Front. Public Health

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Introduction: Understanding determinants of community mobility disability is critical for developing interventions aimed at preventing or delaying disability in older adults. In an effort to understand these determinants, capturing and measuring community mobility has become a key factor. The objectives of this paper are to present and illustrate the signal processing workflow and outcomes that can be extracted from an activity and community mobility measurement approach based on GPS and accelerometer sensor data and 2) to explore the construct validity of the proposed measurement approach using data collected from healthy older adults in free-living conditions.Methods: Personal, functional impairment and environmental variables were obtained by self-report questionnaires in 75 healthy community-living older adults (mean age = 66 ± 7 years old) living on the island of Montreal, QC, Canada. Participants wore, for 14 days during waking hours on the hip, a data logger incorporating a GPS receiver with a 3-axis accelerometer. Time at home ratio (THR), Trips out (TO), Destinations (D), Maximal distance of destinations (MDD), Active time ratio (ATR), Steps (S), Distance in a vehicle (DV), Time in a vehicle (TV), Distance on foot (DF), Time on foot (TF), Ellipse area (EA), and Ellipse maximum distance (EMD) were extracted from the recordings.Results: After applying quality control criteria, the original data set was reduced from 75 to 54 participants (28% attrition). Results from the remaining sample show that under free-living conditions in healthy older adults, location, activity and community mobility outcomes vary across individuals and certain personal variables (age, income, living situation, professional status, vehicle access) have potential mitigating effects on these outcomes. There was a significant (yet small) relationship (rho < 0.40) between self-reported life space and MDD, DV, EA, and EMD.Conclusion: Wearability and usability of the devices used to capture free-living community mobility impact participant compliance and the quality of the data. The construct validity of the proposed approach appears promising but requires further studies directed at populations with mobility impairments.

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Section: Introductionmentioning

confidence: 99%

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors

Boissy

Blamoutier

Brière

et al. 2018

Front. Public Health

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“…Systematic reviews have shown the importance of the measurement of Mobility in acute hospital settings and in elderly patients, because independence in mobility is a key factor in determining discharge after acute hospitalization and has been identified as a predictor of many important outcomes. 25,26…”

Section: Discussionmentioning

confidence: 99%

International Classification of Functioning, Disability, and Health Domains of 60 Physical Functioning Measurement Instruments Used During the Adult Intensive Care Unit Stay: A Scoping Review

2018

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Background There has been a recent surge in the creation and adaptation of instruments to measure physical functioning (PF) in the intensive care unit (ICU). Selecting the right measurement instrument depends on understanding the core constructs that it measures in terms of the International Classification of Functioning, Disability and Health (ICF) domains. Purpose The purpose of this study was to map systematically the ICF domains and subdomains included in the PF measurement instruments used for adult patients during the ICU stay. Data Sources A systematic search was carried out in Cochrane CENTRAL, PubMed, CINAHL, and LILACS as well as a hand search up to May 17, 2017. Study Selection Study selection included all types of research articles that used at least 1 PF measurement instrument in adult patients within the ICU. Data Extraction Study design, year of publication, study population, and the measurement instruments reported were recorded. A consensus of experts analyzed the ICF domains included in each instrument. Data Synthesis We found 181 articles containing 60 PF measurement instruments used during the ICU stay. Twenty-six ICF domains were identified, 38 instruments included Mobility , and 13 included Muscle function . Limitations Studies not written in English or Spanish were excluded. Conclusions There are numerous PF measurement instruments used in adult patients in the ICU. The most frequent ICF domain measured is Mobility . This study highlights the ICF domains contained in the instruments that can be used clinically, providing a complete database of instruments that could facilitate selection of the most appropriate measure based on the patients’ needs.

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“…Mobility status, a distinct aspect of functional ability, may be particularly useful in identifying hospitalized older adults likely to need post-hospital SNF care. Patient mobility can be measured through observed performance-based or patient-reported measures [5–8]. Lacking from the literature is knowledge of which mobility measures in the inpatient setting are predictive of important hospital outcomes.…”

Section: To the Editormentioning

confidence: 99%

Inpatient Mobility Measures As Useful Predictors of Discharge Destination in Hospitalized Older Adults

Pavon

Sloane

Morey

et al. 2017

J American Geriatrics Society

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Patient-Reported Mobility: A Systematic Review

Cited by 19 publications

References 63 publications

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors

International Classification of Functioning, Disability, and Health Domains of 60 Physical Functioning Measurement Instruments Used During the Adult Intensive Care Unit Stay: A Scoping Review

Inpatient Mobility Measures As Useful Predictors of Discharge Destination in Hospitalized Older Adults

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