ArticleBiomedical engineering online2023
Sensor-based assessment of social isolation in community-dwelling older adults: a scoping review.
Article in Biomedical engineering online, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Sensor-Based Technologies for the Detection of Unwanted Loneliness in Older Adults: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Physical literacy in older adults: An evolutionary concept analysis.International journal of nursing sciences · 2026Review
- Potential profiling of social alienation in elderly stroke patients and study of influencing factors.BMC geriatrics · 2025Article
- Multimodal sensor dataset for monitoring older adults post lower limb fractures in community settings.Scientific data · 2025Article
- Relationship between objectively measured conversation time and social behavior in community-dwelling older adults.Frontiers in neurology · 2024Article
- Indoor Group Identification and Localization Using Privacy-Preserving Edge Computing Distributed Camera Network.IEEE journal of indoor and seamless positioning and navigation · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social isolation (SI) is a state of low social interaction with peers associated with various adverse health consequences in older adults living in the community. SI is most often assessed through retrospective self-reports, which can be prone to recall or self-report biases and influenced by stigma. Ambient and wearable sensors have been explored to objectively assess SI based on interactions of a person within the environment and physiological data. However, because this field is in its infancy, there is a lack of clarity regarding the application of sensors and their data in assessing SI and the methods to develop these assessments. To understand the current state of research in sensor-based assessment of SI in older adults living in the community and to make recommendations for the field moving forward, we conducted a scoping review. The aims of the scoping review were to (i) map the types of sensors (and their associated data) that have been used for objective SI assessment, and (ii) identify the methodological approaches used to develop the SI assessment. Using an established scoping review methodology, we identified eight relevant articles. Data from motion sensors and actigraph were commonly applied and compared and correlated with self-report measures in developing objective SI assessments. Variability exists in defining SI, feature extraction and the use of sensors and self-report assessments. Inconsistent definitions and use of various self-report scales for measuring SI create barriers to studying the concept and extracting features to build predictive models. Recommendations include establishing a consistent definition of SI for sensor-based assessment research and development and consider capturing its complexity through innovative domain-specific features.
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Registered trials
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.