Evidence map›Paper›PMID 41952111›Full record

ReviewEuropean review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity2026

Qualitative assessment of mobility in older adults: a scoping review of process-oriented behavioural criteria.

Natalie Lander, Costas Glavas, Anoohya Gandham, Ana Maria Contardo Ayala, L Eduardo Cofré Lizama, Yuxin Zhang, Jackson Fyfe, Tao Zhou, David Scott, Robin M Daly

Abstract readReview
In one paragraph

Review in European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Natalie LanderInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia. natalie.lander@deakin.edu.au.
Costas GlavasInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
Anoohya GandhamInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
Ana Maria Contardo AyalaInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
L Eduardo Cofré LizamaDepartment of Allied Health, School of Health Sciences, Swinburne University of Technology, Hawthorn, Melbourne, Victoria, Australia.
Yuxin ZhangInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
Jackson FyfeInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
Tao ZhouInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
David ScottInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.
Robin M DalyInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.

Funding

Australian Research Council DE240100452
6 · The paper itself

Abstract

BACKGROUND/

objectivesMobility decline is a strong predictor of falls, fractures, and disability in older adults and is associated with sarcopenia, kinesiophobia, reduced physical activity, and poorer quality of life. Early identification is essential to mitigate deterioration. Yet, most clinical assessments emphasise performance outcomes (e.g., time, repetitions) and often overlook early qualitative signs of mobility deterioration. Process-oriented assessments evaluating movement quality may offer greater sensitivity but are seldom used given time, resource, and training constraints. Digital technologies could overcome barriers, but practical evidence-based tools remain limited. This review aimed to identify process-oriented behavioural criteria for qualitatively assessing functional mobility in older adults, establishing a foundation for digital mobility assessments.

methodsFollowing Joanna Briggs Institute and PRISMA-ScR guidelines, six databases (MEDLINE Complete, APA PsycInfo, CINAHL, Sport Discus, Embase, Web of Science) were searched from inception to September 2025. Six reviewers independently screened studies and extracted data. Inductive analysis identified behavioural criteria and tool characteristics.

resultsTwenty-four studies met inclusion criteria. Most assessed balance and gait using ordinal scales. Berg Balance Scale and Dynamic Gait Index showed high reliability and validity; Mini-BEST and POMA demonstrated moderate properties. Feasibility was inconsistently reported. Limitations included moderate clinical burden, ceiling/floor effects, reliance on trained raters, equipment requirements, and lack of a standardised framework.

conclusionsProcess-oriented assessments are limited by inconsistent psychometric quality, feasibility constraints, and a lack of standardisation, highlighting a critical gap in qualitative assessment. SIGNIFICANCE/IMPLICATIONS: Validated process-oriented criteria may enable scalable digital mobility assessment integration, allowing for earlier detection, tailored interventions, reduced falls risk, and streamlined clinical workflows without extensive training or specialised equipment.

Indexed as

Functional mobilityOlder adultsProcess-oriented criteriaQualitative assessment

Identifiers

PMID41952111
PMCPMC13343590

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.